sigmatree_2011_Java_IEEE_Software_Project_Abstracts__2011-2012 by csehk2k12

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									SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, APRIL 2011

DYNAMIC TIME SLOT PARTITIONING FOR MULTIMEDIA
TRANSMISSION IN TWO-HOP CELLULAR NETWORKS

ABSTRACT
In recent years, there has been an exponential increase in the number of mobile
phone users. In addition, a significant growth in the demand for high-rate
multimedia services over wireless networks, such as video conferencing,
multimedia streaming, etc., was noted.
Different solutions were proposed to support high-quality high data rate delivery
to mobile users, including resource allocation techniques for packet-radio-based
next generation cellular networks.
In this paper, an efficient time slot allocation method—Dynamic Time Slot
Partitioning (DTSP) algorithm based on statistical multiplexing is proposed for a
two-hop cellular architecture. In DTSP, the available bandwidth resources are
increased by partitioning each time slot into several minislots wherein different
numbers of minislots are allocated to different users.
The DTSP algorithm is based on asynchronous time-division multiplexing,
wherein users with variable number of packets in their buffers can transmit data
sequentially without any loss in the overall available resources.
The key advantage of DTSP is that it can flexibly adapt to different quality of
service requirements, especially when combined with adaptive modulation. It has
been observed that the system capacity achieved by the DTSP algorithm in the
downlink mode using adaptive modulation is up to 41 percent higher than when
existing solutions are employed.
In addition, DTSP results in significantly lower time for data transmission than the
state-of-the-art region and time partitioning techniques.

INDEX TERMS
Adaptive modulation, cluster-based design, dynamic time slot partitioning,
statistical multiplexing, time-division multiple access, two-hop.

IEEE TRANSACTIONS ON MOBILE COMPUTING, MARCH 2011

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects

EFFICIENT LOCATION TRAINING PROTOCOLS FOR
HETEROGENEOUS SENSOR AND ACTOR NETWORKS

ABSTRACT
In this work, we consider a large-scale geographic area populated by tiny sensors
and some more powerful devices called actors, authorized to organize the
sensors in their vicinity into short-lived, actor-centric sensor networks. The tiny
sensors run on miniature nonrechargeable batteries, are anonymous, and are
unaware of their location.
The sensors differ in their ability to dynamically alter their sleep times. Indeed,
the periodic sensors have sleep periods of predefined lengths, established at
fabrication time; by contrast, the free sensors can dynamically alter their sleep
periods, under program control.
The main contribution of this work is to propose an energy-efficient location
training protocol for heterogeneous actor-centric sensor networks where the
sensors acquire coarse-grain location awareness with respect to the actor in their
vicinity.
Our theoretical analysis, confirmed by experimental evaluation, shows that the
proposed protocol outperforms the best previously known location training
protocols in terms of the number of sleep/awake transitions, overall sensor awake
time, and energy consumption.

INDEX TERMS
Sensor and actor networks, heterogeneous sensors, coarse-grain localization,
location training protocols, localization protocols.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, JUNE 2011

CROSS-LAYER OPTIMIZATION FOR MULTIMEDIA
TRANSPORT OVER MULTICODE CDMA NETWORKS

ABSTRACT
Most previous work on code division multiple access (CDMA) considers the bit
error ratio (BER) at the physical layer and the frame drop ratio (FDR) at the
medium access control layer separately. However, a better system performance,
e.g., in terms of a lower overall frame loss ratio (FLR), can be achieved if BER
and FDR are jointly optimized.
In this paper, we propose a cross-layer optimization scheme called traffic-
adaptive scheme for multicode CDMA operating over a time division multiple
access (TDMA) channel.
Based on the traffic condition and buffer status, this scheme employs a Markov
Decision Process (MDP) to determine the optimal value of the maximum number
of simultaneous data frames that can be transmitted in each time slot of a TDMA
frame so as to minimize the overall FLR of the system.
To facilitate implementation, we also propose an approximation scheme named
the rate adaptive scheme to reduce the computation cost. Simulation and
scheme can significantly reduce FLR, increase the system throughput, and
optimize the packet access delay of the system.
Furthermore, the rate-adaptive scheme can achieve a performance close to the

INDEX TERMS
Multimedia communication, wireless, multicode code division multiple access.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, JUNE 2011

EFFECTIVE SCHEDULING IN INFRASTRUCTURE-BASED

ABSTRACT
In this paper, we investigate a joint scheduling and power control for an
infrastructure-based cognitive radio network (CRN) in coexistence with a cellular
primary radio network (PRN). The PRN uses a set of licensed nonoverlapping
orthogonal frequency channels for transmission.
This set of channels is also accessed in an opportunistic manner by a set of
cognitive radio base stations (CR-BSs) to support secondary users (SUs). The
problem is formulated to maximize the spectrum utilization of SUs without
causing excessive interference to active primary users (PUs) of the PRN. In
addition, all the serviced SUs must meet a certain Quality of Service (QoS), such
as satisfying a predefined signal to interference noise ratio (SINR).
A centralized solution for joint scheduling and power control is derived to make
the global accessing decision for all unserved SUs. With the assumption that the
knowledge of all subscribers is available, a coordinator of the CRN can use the
joint scheduling and power control algorithm to maximize the spectrum utilization
of serviced SUs by solving a mixed-integer linear programming (MILP) with an
NP-hard complexity.
To avoid the NP-hard complexity, we propose a suboptimal heuristic greedy
algorithm that can be obtained at a much lower complexity based on the coloring
interference graph among unserved SUs effected by serviced SUs and active
PUs. Its superior performance over the existing algorithms is demonstrated
through simulations.

INDEX TERMS
Cognitive radio, opportunistic spectrum allocation, scheduling, power control,
interference graph.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, MARCH 2011

DESIGN AND PERFORMANCE ANALYSIS OF MOBILITY
MANAGEMENT SCHEMES BASED ON POINTER
FORWARDING FOR WIRELESS MESH NETWORKS

ABSTRACT
We propose efficient mobility management schemes based on pointer forwarding
for wireless mesh networks (WMNs) with the objective to reduce the overall
network traffic incurred by mobility management and packet delivery.
The proposed schemes are per-user-based, i.e., the optimal threshold of the
forwarding chain length that minimizes the overall network traffic is dynamically
determined for each individual mobile user, based on the user’s specific mobility
and service patterns.
We develop analytical models based on stochastic Petri nets to evaluate the
performance of the proposed schemes. We demonstrate that there exists an
optimal threshold of the forwarding chain length, given a set of parameters
characterizing the specific mobility and service patterns of a mobile user.
We also demonstrate that our schemes yield significantly better performance than
schemes that apply a static threshold to all mobile users. A comparative analysis
shows that our pointer forwarding schemes outperform routing-based mobility
management protocols for WMNs, especially for mobile Internet applications
characterized by large traffic asymmetry for which the downlink packet arrival
rate is much higher than the uplink packet arrival rate.

INDEX TERMS
Mobility management, pointer forwarding, wireless mesh networks, performance
analysis, stochastic Petri net.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, APRIL 2011

A COOPERATIVE CLUSTERING PROTOCOL FOR ENERGY
SAVING OF MOBILE DEVICES WITH WLAN AND
BLUETOOTH INTERFACES

ABSTRACT
One of the most widely used wireless communication standards is a Wireless
Local Area Network (WLAN) (IEEE 802.11). However, WLAN has a serious power
consumption problem. In this paper, we propose a novel energy saving approach
that exploits the multiradio feature of recent mobile devices equipped with WLAN
and Bluetooth interfaces.
Unlike previous approaches, our work is based on clustering. In our work, a
cluster is a Bluetooth Personal Area Network (PAN), which consists of one
cluster head and several regular nodes. The cluster head acts as a gateway
between the PAN and the WLAN, enabling the regular nodes to access the WLAN
infrastructure via low-power Bluetooth.
We present a distributed clustering protocol, Cooperative Networking protocol
(CONET), which dynamically reforms clusters according to each node’s
bandwidth requirement, energy use, and application type. CONET does not
require modifications of existing wireless infrastructures because clustering is
performed independently of WLAN access points.
We implemented the CONET prototype with four wearable computing devices to
evaluate the performance on real hardware. We also simulated CONET for large
networks of more than 100 mobile nodes. Both results demonstrate that our
approach is effective in reducing the power consumption of WLAN.

INDEX TERMS
Wireless communication, protocol architecture, multiradio, energy efficiency,
clustering.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, JUNE 2011

AUTONOMOUS DEPLOYMENT OF HETEROGENEOUS
MOBILE SENSORS

ABSTRACT
In this paper, we address the problem of deploying heterogeneous mobile
sensors over a target area. Traditional approaches to mobile sensor deployment
are specifically designed for homogeneous networks. Nevertheless, network and
device homogeneity is an unrealistic assumption in most practical scenarios, and
previous approaches fail when adopted in heterogeneous operative settings.
For this reason, we introduce VorLag, a generalization of the Voronoi-based
approach which exploits the Laguerre geometry. We theoretically prove the
appropriateness of our proposal to the management of heterogeneous networks.
In addition, we demonstrate that VorLag can be extended to deal with
dynamically generated events or uneven energy depletion due to
communications.
Finally, by means of simulations, we show that VorLag provides a very stable
sensor behavior, with fast and guaranteed termination and moderate energy
consumption. We also show that VorLag performs better than its traditional
counterpart and other methods based on virtual forces.

INDEX TERMS
Device heterogeneity, self-deployment, Voronoi-Laguerre diagrams.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, JUNE 2011

A CONTROL-THEORETIC APPROACH TO DISTRIBUTED
OPTIMAL CONFIGURATION OF 802.11 WLANS

ABSTRACT
The optimal configuration of the contention parameters of a WLAN depends on
the network conditions in terms of number of stations and the traffic they
generate. Following this observation, a considerable effort in the literature has
been devoted to the design of distributed algorithms that optimally configure the
WLAN parameters based on current conditions.
In this paper, we propose a novel algorithm that, in contrast to previous proposals
which are mostly based on heuristics, is sustained by mathematical foundations
from multivariable control theory. A key advantage of the algorithm over existing
approaches is that it is compliant with the 802.11 standard and can be
implemented with current wireless cards without introducing any changes into the
hardware or firmware.
We study the performance of our proposal by means of theoretical analysis,
simulations, and a real implementation. Results show that the algorithm
substantially outperforms previous approaches in terms of throughput and delay.

INDEX TERMS
Wireless LAN, IEEE 802.11, DCF, adaptive MAC, distributed algorithm,
multivariable control theory.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, MARCH 2011

DELAY-SENSITIVE PERVASIVE APPLICATIONS

ABSTRACT
In this paper, we introduce a delay-sensitive service that involves transmitting
large amounts of location-based data to nodes at multiple locations. Given a
limited amount of access points (APs) and an abundance of service requests that
result from the nodes moving around, a typical content delivery service would
inevitably introduce considerable delay.
To solve this problem, we analyze the movement pattern of mobile nodes and
approximate it as a semi-Markov process. Based on this model, we explore
different components of the underlying service delay and propose that APs
should use a multicast strategy to minimize the queuing delay component.
Furthermore, we demonstrate the feasibility of employing nodes, which already
have their own local copies of location-relevant data, to relay such data to other
nodes by employing one or multiple communication channels.
Lastly, we examine the resulting algorithms and study their performance relative
to baseline content-delivery schemes through simulations.

INDEX TERMS
Location-dependent    and   sensitive,   pervasive   computing,   wireless   sensor
networks.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, APRIL 2011

A DISTRIBUTED AND SCALABLE TIME SLOT
ALLOCATION PROTOCOL FOR WIRELESS SENSOR
NETWORKS

ABSTRACT
There are performance deficiencies that hamper the deployment of Wireless
Sensor Networks (WSNs) in critical monitoring applications. Such applications
are characterized by considerable network load generated as a result of sensing
some characteristics of the monitored system.
Excessive packet collisions lead to packet losses and retransmissions, resulting
in significant overhead costs and latency. In order to address this issue, we
introduce a distributed and scalable scheduling access scheme that mitigates
high data loss in data-intensive sensor networks and can also handle some
mobility.
Our approach alleviates transmission collisions by employing virtual grids that
adopt Latin Squares characteristics to time slot assignments. We show that our
algorithm derives conflictfree time slot allocation schedules without incurring
Furthermore, we verify the effectiveness of our protocol by simulation
experiments. The results demonstrate that our technique can efficiently handle
sensor mobility with acceptable data loss, low packet delay, and low overhead.

INDEX TERMS
Access scheduling, wireless sensor networks, data-intensive applications,
topology changes.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, MAY 2011

DESIGN AND PERFORMANCE OF AN OPTIMAL INERTIAL
POWER HARVESTER FOR HUMAN-POWERED DEVICES

ABSTRACT
We present an empirical study of the long-term practicality of using human
motion to generate operating power for bodymounted consumer electronics and
health sensors. We have collected a large continuous acceleration data set from
eight experimental subjects going about their normal daily routine for three days
each.
Each subject is instrumented with a data collection apparatus that simultaneously
logs 3-axis, 80 Hz acceleration data from six body locations. We use this data set
to optimize a firstprinciples physical model of the commonly used velocity
damped resonant generator (VDRG) by selecting physical parameters such as
resonant frequency and damping coefficient to maximize the harvested power.
Our results show that with reasonable assumptions on size, mass, placement,
and efficiency of VDRG harvesters, most body-mounted wireless sensors and
even some consumer electronics devices can be powered continuously and
indefinitely from everyday motion.
We have optimized the power harvesters for each individual and for each body
location. In addition, we present the potential of designing a damping- and
frequency-tunable power harvester that could mitigate the power reduction of a
generator generalized for “average” subjects.
We present the full details on the collection of the acceleration data sets, the
development of the VDRG model, and a numerical simulator, and discuss some
of the future challenges that remain in this promising field of research.

INDEX TERMS
Human power harvesting, inertial generator, optimal design, tunable generator,
human-powered device.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, MAY 2011

RESOURCE MANAGEMENT FOR VOWLAN

ABSTRACT
This paper examines two specific aspects of resource management in Wireless
Local Area Networks (WLANs)—Call Admission Control (CAC) and handling of
Link Adaptation (LA) events. A self-consistent system to manage these for Voice
over Internet Protocol (VoIP) over an IEEE 802.11 WLAN is presented.
The proposed CAC scheme is based on the Endpoint Admission Control (EAC)
paradigm, where the endpoints probe the network to determine if the call can be
supported with acceptable Quality of Service (QoS).
The proposed scheme was evaluated on an experimental testbed and test results
configurations. The scheme also determines if LA has resulted in the system
becoming congested and, if so, the voice codec of the handset which has
undergone LA is adapted so as to restore the system to its earlier state, thereby
alleviating the congestion.
The proposed scheme was evaluated on the experimental testbed and test
results show that the codec adaptation scheme was very effective at overcoming
the effects of LA for VoIP over WLAN.

INDEX TERMS

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                          IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, MAY 2011

OPTIMAL STOCHASTIC LOCATION UPDATES IN MOBILE

ABSTRACT
We consider the location service in a mobile ad-hoc network (MANET), where each node
needs to maintain its location information by 1) frequently updating its location
information within its neighboring region, which is called neighborhood update (NU), and
2) occasionally updating its location information to certain distributed location server in
the network, which is called location server update (LSU).
The trade off between the operation costs in location updates and the performance
losses of the target application due to location inaccuracies (i.e., application costs)
imposes a crucial question for nodes to decide the optimal strategy to update their
location information, where the optimality is in the sense of minimizing the overall costs.
In this paper, we develop a stochastic sequential decision framework to analyze this
problem.
Under a Markovian mobility model, the location update decision problem is modeled as
a Markov Decision Process (MDP). We first investigate the monotonicity properties of
optimal NU and LSU operations with respect to location inaccuracies under a general
cost setting.
Then, given a separable cost structure, we show that the location update decisions of
NU and LSU can be independently carried out without loss of optimality, i.e., a
separation property.
From the discovered separation property of the problem structure and the monotonicity
properties of optimal actions, we find that 1) there always exists a simple optimal
threshold-based update rule for LSU operations; 2) for NU operations, an optimal
threshold-based update rule exists in a low-mobility scenario.
In the case that no a priori knowledge of the MDP model is available, we also introduce
a practical model-free learning approach to find a near-optimal solution for the problem.

INDEX TERMS
Location update, mobile ad hoc networks, Markov decision processes, least-
squares policy iteration

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, JUNE 2011

MOBILE SAMPLING OF SENSOR FIELD DATA USING

ABSTRACT
Mobile objects can be used to gather samples from a sensor field. Civilian
vehicles or even human beings equipped with proper wireless communication
devices can be used as mobile sinks that retrieve sensor-data from sampling
points within a large sensor field.
A key challenge is how to gather the sensor data in a manner that is energy
efficient with respect to the sensor nodes that serve as sources of the sensor
data. In this paper, an algorithmic technique called Band-based Directional
Broadcast is introduced to control the direction of broadcasts that originate from
sensor nodes.
The goal is to direct each broadcast of sensor data toward the mobile sink, thus
reducing costly forwarding of sensor data packets. The technique is studied by
simulations that consider energy consumption and data deliverability.

INDEX TERMS
Sensor data sampling, mobile object, directional broadcast, sensor networks.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, JUNE 2011

FAST DETECTION OF MOBILE REPLICA NODE ATTACKS
IN WIRELESS SENSOR NETWORKS USING SEQUENTIAL
HYPOTHESIS TESTING

ABSTRACT
Due to the unattended nature of wireless sensor networks, an adversary can
capture and compromise sensor nodes, make replicas of them, and then mount a
variety of attacks with these replicas. These replica node attacks are dangerous
because they allow the attacker to leverage the compromise of a few nodes to
exert control over much of the network.
Several replica node detection schemes have been proposed in the literature to
defend against such attacks in static sensor networks. However, these schemes
rely on fixed sensor locations and hence do not work in mobile sensor networks,
where sensors are expected to move.
In this work, we propose a fast and effective mobile replica node detection
scheme using the Sequential Probability Ratio Test. To the best of our
knowledge, this is the first work to tackle the problem of replica node attacks in
mobile sensor networks.
We show analytically and through simulation experiments that our scheme
detects mobile replicas in an efficient and robust manner at the cost of

INDEX TERMS
Replica detection, sequential analysis, mobile sensor networks, security.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, APRIL 2011

MINIMUM BANDWIDTH RESERVATIONS FOR PERIODIC
STREAMS IN WIRELESS REAL-TIME SYSTEMS

Reservation-based (as opposed to contention-based) channel access in WLANs
provides predictable and deterministic transmission and is therefore able to
provide timeliness guarantees for wireless and embedded real-time applications.
Also, reservation-based channel access is energy-efficient since a wireless
adaptor is powered on only during its exclusive channel access times. While
scheduling for Quality of Service at the central authority (e.g., base station) has
received extensive attention, the problem of determining the actual resource
requirements of an individual node in a wireless real-time system has been
largely ignored.
This work aims at finding the minimum channel bandwidth reservation that meets
the real-time constraints of all periodic streams of a given node. Keeping the
bandwidth reservation of a node to a minimum leads to reduced energy and
resource requirements and leaves more bandwidth for future reservations by
other nodes.
To obtain a solution to the minimum bandwidth reservation problem, we transform
it to a generic uniprocessor task schedulability problem, which is then addressed
using a generic algorithm. This algorithm works for a subclass of priority-driven
packet scheduling policies, including three common ones: fixed-priority, EDF, and
FIFO.
Moreover, we then specialize the generic algorithm to these three policies
according to their specific characteristics. Their computation complexities and
bandwidth reservation efficiencies are evaluated and guidelines for choosing
scheduling policies and stream parameters are presented.

INDEX TERMS
Bandwidth reservation, schedulability test, earliest deadline first, fixed-priority,
first-in-first-out, medium access control, real time, wireless.

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects

IEEE TRANSACTIONS ON MOBILE COMPUTING
APRIL 2011

ON THE INFORMATION FLOW REQUIRED
FOR TRACKING CONTROL IN
NETWORKS OF MOBILE SENSING AGENTS

ABSTRACT
We design controllers that permit mobile agents with distributed or
networked sensing capabilities to track (follow) desired trajectories,
identify what trajectory information must be distributed to each agent
for tracking, and develop methods to minimize the communication
needed for the trajectory information distribution.

INDEX TERMS
Cooperative control, dynamical networks, tracking

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                           IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, JUNE 2011

MULTICAST THROUGHPUT FOR HYBRID WIRELESS
NETWORKS UNDER GAUSSIAN CHANNEL MODEL

ABSTRACT
We study the multicast capacity for hybrid wireless networks consisting of ordinary ad
hoc nodes and base stations under Gaussian Channel model, which generalizes both
the unicast and broadcast capacities for hybrid wireless networks.
Assume that all ordinary ad hoc nodes transmit at a constant power P, and the power
decays along the path, with attenuation exponent > 2. The data rate of a transmission
is determined by the Signal to Interference plus Noise Ratio (SINR) at the receiver as
Blogð1 þ SINRÞ.
The ordinary ad hoc nodes are placed in the square region AðaÞ of area a according to
a Poisson point process of intensity n=a. Then, m additional base stations (BSs) acting
as the relaying communication gateways are placed regularly in the region AðaÞ, and
are connected by a high-bandwidth wired network. Let a ¼ n and a ¼ 1, we construct
the hybrid extended network (HEN) and hybrid dense network (HDN), respectively. We
choose randomly and independently ns ordinary ad hoc nodes to be the sources of
multicast sessions.
We assume that each multicast session has nd randomly chosen terminals. Three broad
categories of multicast strategies are proposed. The first one is the hybrid strategy, i.e.,
the multihop scheme with BS-supported, which further consists of two types of
strategies called connectivity strategy and percolation strategy, respectively.
The second one is the ordinary ad hoc strategy, i.e., the multihop scheme without any
BS-supported. The third one is the classical BS-based strategy under which any
communication between two ordinary ad hoc nodes is relayed by some specific BSs.
According to the different scenarios in terms of m, n, and nd, we select the optimal
scheme from the three categories of strategies, and derive the achievable multicast
throughput based on the optimal decision.

INDEX TERMS
Wireless hybrid networks, wireless ad hoc networks, multicast throughput,
random networks, multicast capacity, Gaussian channel mode

Sigmatree Solutions India Pvt. Ltd., #5 Thanappa Enclave, Sirur Park Road,
Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
www.sigmatreesolutions.com E-mail: projectsban@sigmatreesolutions.com
SIGMATREE SOLUTIONS                          IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE TRANSACTIONS ON MOBILE COMPUTING, MARCH 2011

ON THE DESIGN OF OPPORTUNISTIC MAC PROTOCOLS
FOR MULTIHOP WIRELESS NETWORKS WITH
BEAMFORMING ANTENNAS

ABSTRACT
Beamforming antennas promise a significant increase in the spatial reuse of the wireless
medium when deployed in multihop wireless networks. However, existing directional
Medium Access Control (MAC) protocols with the default binary exponential backoff
mechanism are not capable of fully exploiting the offered potential.
In this paper, we discuss various issues involved in the design of MAC protocols specific
for beamforming antennas. Based on our discussion, we argue that the traditional binary
exponential backoff mechanism limits the possible spatial reuse and aggravates some
beamforming-related problems such as deafness and headof- line blocking.
To grasp the transmission opportunities offered by beamforming antennas, we design an
Opportunistic Directional MAC (OPDMAC) protocol for multihop wireless networks. The
OPDMAC protocol employs a novel backoff mechanism in which the node is not forced
to undergo idle backoff after a transmission failure but can rather take the opportunity of
transmitting other outstanding packets in other directions.
This mechanism minimizes the idle waiting time and increases the channel utilization
significantly and thereby enables OPDMAC to enhance the spatial reusability of the
wireless medium and reduce the impact of the deafness problem without additional
overhead. Through extensive simulations, we demonstrate that OPDMAC enhances the
performance in terms of throughput, delay, packet delivery ratio, and fairness.
To further improve its performance, we discuss and evaluate the benefits of carefully
choosing some protocol parameters instead of using the default values commonly used
by other directional MAC protocols.

INDEX TERMS
Beamforming antennas, medium access control, multihop wireless networks,
spatial reuse.

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IEEE TRANSACTIONS ON MOBILE COMPUTING, MAY 2011

INTERFERENCE-AWARE ROUTING IN WIRELESS
MULTIHOP NETWORKS

ABSTRACT
Interference is an inherent characteristic of wireless (multihop) communications.
Adding interference-awareness to important control functions, e.g., routing, could
significantly enhance the overall network performance. Despite some initial
efforts, it is not yet clearly understood how to best capture the effects of
interference in routing protocol design.
Most existing proposals aim at inferring its effect by actively probing the link.
However, active probe measurements impose an overhead and may often
misrepresent the link quality due to their interaction with other networking
functions. Therefore, in this paper we follow a different approach and:
1) propose a simple yet accurate analytical model for the effect of interference
on data reception probability, based only on passive measurements and
information locally available at the node;
2) use this model to design an efficient interference-aware routing protocol that
performs as well as probing-based protocols, yet avoids all pitfalls related to
active probe measurements.
To validate our proposal, we have performed experiments in a real testbed, setup
in our indoor office environment. We show that the analytical predictions of our
interference model exhibit good match with both experimental results as well as
more complicated analytical models proposed in related literature.
Furthermore, we demonstrate that a simple probeless routing protocol based on
our model performs at least as good as well-known probe-based routing protocols
in a large set of experiments including both intraflow and interflow interference.

INDEX TERMS
Wireless networks, interference model, interference-aware routing, routing metric.

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IEEE TRANSACTIONS ON MOBILE COMPUTING, MAY 2011

MAC LAYER THROUGHPUT ESTIMATION IN IMPULSE-RADIO
UWB NETWORKS

ABSTRACT
The inherent channel characteristics of impulse-based UWB networks affect the
MAC layer performance significantly. Most previous studies on evaluating MAC
protocols are based on prolonged simulations and do not account for the multiple
access interference due to multipath delay spread.
In this work, we develop CTU, an analytical framework for Capturing the
Throughput dependencies in UWB networks, while taking into account the PHY
layer effects.
The key attributes of CTU are:
1) It is modular; it can be easily modified to provide a basis for evaluating a wide
range of MAC protocols for impulse-based UWB networks. The only
requirements are that the MAC protocol under study be based on time-
hopping and the modulation scheme be pulse position modulation; these are
common design decisions in UWB networks.
2) It considers the channel characteristics in addition to MAC layer effects; CTU
correlates probabilistically the multipath delay profile of the channel with the
packet error rate. We employ CTU to evaluate the performance of different
generic medium access procedure.
We compare the results with those from extensive simulations and show the high
accuracy of CTU. We use CTU to assess the impact of various system
parameters on the MAC layer performance; we make several interesting
observations that are discussed in depth.

INDEX TERMS
Ultrawide band (UWB), wireless communications, multipath delay spread,
modulation.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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IEEE TRANSACTIONS ON MOBILE COMPUTING, JUNE 2011

TRAFFIC-DIFFERENTIATION-BASED MODULAR QOS
LOCALIZED ROUTING FOR WIRELESS SENSOR
NETWORKS

ABSTRACT
A new localized quality of service (QoS) routing protocol for wireless sensor
networks (WSN) is proposed in this paper. The proposed protocol targets WSN’s
applications having different types of data traffic. It is based on differentiating
QoS requirements according to the data type, which enables to provide several
and customized QoS metrics for each traffic category.
With each packet, the protocol attempts to fulfill the required data-related QoS
metric(s) while considering power efficiency. It is modular and uses geographical
information, which eliminates the need of propagating routing information. For
link quality estimation, the protocol employs distributed, memory and computation
efficient mechanisms.
It uses a multisink single-path approach to increase reliability. To our knowledge,
this protocol is the first that makes use of the diversity in data traffic while
considering latency, reliability, residual energy in sensor nodes, and transmission
power between nodes to cast QoS metrics as a multiobjective problem.
The proposed protocol can operate with any medium access control (MAC)
protocol, provided that it employs an acknowledgment (ACK) mechanism.
Extensive simulation study with scenarios of 900 nodes shows the proposed
protocol outperforms all comparable state-of-the-art QoS and localized routing
protocols. Moreover, the protocol has been implemented on sensor motes and
tested in a sensor network testbed.

INDEX TERMS
Wireless sensor networks, quality of service, geographical routing, distributed
protocols.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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IEEE TRANSACTIONS ON MOBILE COMPUTING, MAY 2011

QOS-AWARE ROUTING AND ADMISSION CONTROL IN
MANETS

ABSTRACT
Providing quality of service (QoS) assurances in a mobile ad hoc network
(MANET) is difficult due to node mobility, contention for channel access, a lack of
centralized co-ordination, and the unreliable nature of the wireless channel.
A QoS-aware routing (QAR) protocol and an admission control (AC) protocol are
two of the most important components of a system attempting to provide QoS
guarantees in the face of the above mentioned difficulties faced. Many QAR and
AC-based solutions have been proposed, but such network layer solutions are
often designed and studied with idealized lower layer models in mind.
This means that existing solutions are not designed for dealing with practical
link transmission rates. This paper proposes and evaluates new solutions for
improving the performance of QAR and AC protocols in the face of mobility,
It is found that proactively maintaining backup routes for active sessions,
noticeably improve the reliability of assured throughput services.

INDEX TERMS

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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IEEE TRANSACTIONS ON MOBILE COMPUTING, MARCH 2011

PROCESSING CONTINUOUS RANGE QUERIES WITH
SPATIOTEMPORAL TOLERANCE

ABSTRACT
Continuous queries are often employed to monitor the locations of mobile objects
(MOs), which are determined by sensing devices like GPS receivers.
In this paper, we tackle two challenges in processing continuous range queries
(CRQs): coping with data uncertainty inherently associated with location data,
and reducing the energy consumption of battery-powered MOs. We propose the
concept of spatiotemporal tolerance for CRQ to relax a query’s accuracy
requirements in terms of a maximal acceptable error. Unlike previous works, our
definition considers tolerance in both the spatial and temporal dimensions, which
offers applications more flexibility in specifying their individual accuracy
requirements.
As we will show, these tolerance bounds can provide well-defined query
semantics in spite of different sources of data uncertainty. In addition, we present
efficient algorithms that carefully control when an MO should sense or report a
location, while satisfying these tolerances.
Thereby, we particularly reduce the number of position sensing operations
substantially, which constitute a considerable source of energy consumption.
Extensive simulations confirm that the proposed algorithms result in large energy
savings compared to nontolerant query processing.

INDEX TERMS
Tracking mobile objects, continuous queries, distributed processing, data
uncertainty, energy consumption.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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IEEE TRANSACTIONS ON MOBILE COMPUTING, MARCH 2011

SCALABLE LOCALIZATION WITH MOBILITY PREDICTION
FOR UNDERWATER SENSOR NETWORKS

ABSTRACT
Due to harsh aqueous environments, non-negligible node mobility and large
network scale, localization for large-scale mobile underwater sensor networks is
very challenging. In this paper, by utilizing the predictable mobility patterns of
underwater objects, we propose a scheme, called Scalable Localization scheme
with Mobility Prediction (SLMP), for underwater sensor networks.
In SLMP, localization is performed in a hierarchical way, and the whole
localization process is divided into two parts: anchor node localization and
ordinary node localization. During the localization process, every node predicts
its future mobility pattern according to its past known location information, and it
can estimate its future location based on the predicted mobility pattern.
Anchor nodes with known locations in the network will control the localization
process in order to balance the trade-off between localization accuracy,
localization coverage, and communication cost.
We conduct extensive simulations, and our results show that SLMP can greatly
reduce localization communication cost while maintaining relatively high
localization coverage and localization accuracy.

INDEX TERMS
Network architecture and design, network communications, network protocols,
applications, miscellaneous, localization, underwater sensor networks.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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IEEE TRANSACTIONS ON MOBILE COMPUTING, MAY 2011

SECURE HIGH-THROUGHPUT MULTICAST ROUTING IN
WIRELESS MESH NETWORKS

ABSTRACT
Recent work in multicast routing for wireless mesh networks has focused on
metrics that estimate link quality to maximize throughput. Nodes must collaborate
in order to compute the path metric and forward data. The assumption that all
nodes are honest and behave correctly during metric computation, propagation,
and aggregation, as well as during data forwarding, leads to unexpected
consequences in adversarial networks where compromised nodes act
maliciously.
In this work, we identify novel attacks against high throughput multicast protocols
in wireless mesh networks. The attacks exploit the local estimation and global
aggregation of the metric to allow attackers to attract a large amount of traffic.
We show that these attacks are very effective against multicast protocols based
on high-throughput metrics.
We conclude that aggressive path selection is a double-edged sword: While it
maximizes throughput, it also increases attack effectiveness in the absence of
defense mechanisms. Our approach to defend against the identified attacks
combines measurement-based detection and accusation-based reaction
techniques. The solution accommodates transient network variations and is
resilient against attempts to exploit the defense mechanism itself.
A detailed security analysis of our defense scheme establishes bounds on the
impact of attacks. We demonstrate both the attacks and our defense using
ODMRP, a representative multicast protocol for wireless mesh networks, and
SPP, an adaptation of the well-known ETX unicast metric to the multicast setting.

INDEX TERMS
Wireless mesh networks, high-throughput metrics, secure multicast routing,
metric manipulation attacks, Byzantine attacks.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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IEEE TRANSACTIONS ON MOBILE COMPUTING, APRIL 2011

THROUGHPUT OPTIMIZATION IN MOBILE BACKBONE
NETWORKS

ABSTRACT
This paper describes new algorithms for throughput optimization in a mobile
backbone network. This hierarchical communication framework combines mobile
backbone nodes, which have superior mobility and communication capability, with
regular nodes, which are constrained in mobility and communication capability.
An important quantity of interest in mobile backbone networks is the number of
regular nodes that can be successfully assigned to mobile backbone nodes at a
given throughput level. This paper develops a novel technique for maximizing this
quantity in networks of fixed regular nodes using mixed-integer linear
programming (MILP).
The MILP-based algorithm provides a significant reduction in computation time
compared to existing methods and is computationally tractable for problems of
moderate size. An approximation algorithm is also developed that is appropriate
for largescale problems.
This paper presents a theoretical performance guarantee for the approximation
algorithm and also demonstrates its empirical performance. Finally, the mobile
backbone network problem is extended to include mobile regular nodes, and
exact and approximate solution algorithms are presented for this extension.

INDEX TERMS
Wireless sensor networks, mobile communication systems.

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SIGMATREE SOLUTIONS                          IEEE PROJECTS 2011-12
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IEEE TRANSACTIONS ON MOBILE COMPUTING, APRIL 2011

SUPPORTING EFFICIENT AND SCALABLE
MULTICASTING OVER MOBILE AD HOC NETWORKS

ABSTRACT
Group communications are important in Mobile Ad hoc Networks (MANETs). Multicast is
an efficient method for implementing group communications. However, it is challenging
to implement efficient and scalable multicast in MANET due to the difficulty in group
membership management and multicast packet forwarding over a dynamic topology.
We propose a novel Efficient Geographic Multicast Protocol (EGMP). EGMP uses a
virtual-zone-based structure to implement scalable and efficient group membership
management. A networkwide zone-based bidirectional tree is constructed to achieve
more efficient membership management and multicast delivery.
The position information is used to guide the zone structure building, multicast tree
construction, and multicast packet forwarding, which efficiently reduces the overhead for
route searching and tree structure maintenance. Several strategies have been proposed
to further improve the efficiency of the protocol, for example, introducing the concept of
zone depth for building an optimal tree structure and integrating the location search of
group members with the hierarchical group membership management.
Finally, we design a scheme to handle empty zone problem faced by most routing
protocols using a zone structure. The scalability and the efficiency of EGMP are
evaluated through simulations and quantitative analysis.
Our simulation results demonstrate that EGMP has high packet delivery ratio, and low
control overhead and multicast group joining delay under all test scenarios, and is
scalable to both group size and network size. Compared to Scalable Position-Based
Multicast (SPBM) [20], EGMP has significantly lower control overhead, data
transmission overhead, and multicast group joining delay.

INDEX TERMS
Routing, wireless networks, mobile ad hoc networks, multicast, protocol

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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IEEE TRANSACTIONS ON MOBILE COMPUTING, APRIL 2011

SPATIAL-TEMPORAL COVERAGE OPTIMIZATION IN
WIRELESS SENSOR NETWORKS

ABSTRACT
Mission-driven sensor networks usually have special lifetime requirements.
However, the density of the sensors may not be large enough to satisfy the
coverage requirement while meeting the lifetime constraint at the same time.
Sometimes, coverage has to be traded for network lifetime. In this paper, we
study how to schedule sensors to maximize their coverage during a specified
Unlike sensor deployment, where the goal is to maximize the spatial coverage,
our objective is to maximize the spatialtemporal coverage by scheduling sensors’
activity after they have been deployed. Since the optimization problem is NP-
hard, we first present a centralized heuristic whose approximation factor is
proved to be 1 2 , and then, propose a distributed parallel optimization protocol
(POP). In POP, nodes optimize their schedules on their own but converge to local
optimality without conflict with one another.
Theoretical and simulation results show that POP substantially outperforms other
schemes in terms of network lifetime, coverage redundancy, convergence time,
and event detection probability.

INDEX TERMS
Wireless sensor network, coverage, sensor scheduling, distributed protocol,
parallel algorithm

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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IEEE TRANSACTIONS ON MOBILE COMPUTING, JUNE 2011

THE HIDENETS HOLISTIC APPROACH FOR THE
ANALYSIS OF LARGE CRITICAL MOBILE SYSTEMS

ABSTRACT
Dealing with large, critical mobile systems and infrastructures where ongoing
changes and resilience are paramount leads to very complex and difficult
challenges for system evaluation.
These challenges call for approaches that are able to integrate several evaluation
methods for the quantitative assessment of QoS indicators which have been
applied so far only to a limited extent. In this paper, we propose the holistic
evaluation framework developed during the recently concluded FP6-HIDENETS
project.
It is based on abstraction and decomposition, and it exploits the interactions
among different evaluation techniques including analytical, simulative, and
experimental measurement approaches, to manage system complexity.
The feasibility of the holistic approach for the analysis of a complete end-to-end
scenario is first illustrated presenting two examples where mobility simulation is
used in combination with stochastic analytical modeling, and then through the
development and implementation of an evaluation workflow integrating several
tools and model transformation steps.

INDEX TERMS
Computer systems organization, communication/networking and information
technology, mobile computing, mobile communication systems, computing
methodologies, simulation, modeling, and visualization, model development,
modeling methodologies, computer applications, mobile applications, pervasive
computing.

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SIGMATREE SOLUTIONS                         IEEE PROJECTS 2011-12
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IEEE/ACM TRANSACTIONS ON NETWORKING, APRIL 2011

LICKLIDER TRANSMISSION PROTOCOL (LTP)-BASED
DTN FOR CISLUNAR COMMUNICATIONS

ABSTRACT
Delay/disruption-tolerant networking (DTN) technology offers a new solution to highly
stressed communications in space environments, especially those with long link delay
and frequent link disruptions in deep-space missions. To date, little work has been done
in evaluating the performance of the available “convergence layer” protocols of DTN,
especially the Licklider Transmission Protocol (LTP), when they are applied to an
interplanetary Internet (IPN).
In this paper, we present an experimental evaluation of the Bundle Protocol (BP)
running over various “convergence layer” protocols in a simulated cislunar
communications environment characterized by varying degrees of signal propagation
delay and data loss.
We focus on the LTP convergence layer (LTPCL) adapter running on top ofUDP/IP
(i.e.,BP/LTPCL/UDP/IP). The performance of BP/LTPCL/UDP/IP in realistic ?le transfers
over a PC-based network test bed is compared to that of two other DTN protocol stack
options, BP/TCPCL/TCP/IP and BP/UDPCL/UDP/IP. A statistical method of -test is also
used for analysis of the experimental results.
The experiment results show that LTPCL has a significant performance advantage over
Transmission Control Protocol convergence layer (TCPCL) for link delays longer than
4000 ms regardless of the bit error rate (BER). For a very lossy channel with a BER of
around 10, LTPCL has a significant good put advantage over TCPCL at all the link delay
levels studied, with an advantage of around 3000 B/s for delays longer than 1500 ms.
LTPCL has a consistently significant goodput advantage over UDPCL, around 2500–
3000 B/s, at all levels of link delays and BERs.

INDEX TERMS—Bundle Protocol (BP), delay-tolerant networking (DTN),
interplanetary Internet (IPN), Licklider Transmission Protocol convergence layer
(LTPCL), satellite communications, Transmission Control Protocol convergence
layer (TCPCL).

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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IEEE/ACM TRANSACTIONS ON NETWORKING, FEBRUARY 2011

FORWARD CORRECTION AND FOUNTAIN CODES IN
DELAY-TOLERANT NETWORKS

ABSTRACT
Delay-tolerant ad hoc networks leverage the mobility of relay nodes to
compensate for lack of permanent connectivity and thus enable communication
between nodes that are out of range of each other.
To decrease delivery delay, the information to be delivered is replicated in the
network. Our objective in this paper is to study a class of replication mechanisms
that include coding in order to improve the probability of successful delivery
within a given time limit.
We propose an analytical approach that allows to quantify tradeoffs between
resources and performance measures (energy and delay). We study the effect of
coding on the performance of the network while optimizing parameters that
govern routing. Our results, based on ?uid approximations, are compared to
simulations that validate the model.

INDEX TERMS
Delay-tolerant networks (DTNs), forward correction, fountain codes, mobile ad
hoc networks.

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SIGMATREE SOLUTIONS                        IEEE PROJECTS 2011-12
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IEEE/ACM TRANSACTIONS ON NETWORKING, FEBRUARY 2011

FAST SIMULATION OF SERVICE AVAILABILITY IN MESH
NETWORKS WITH DYNAMIC PATH RESTORATION

ABSTRACT
A fast simulation technique based on importance sampling is developed for the
analysis of path service availability in mesh networks with dynamic path
restoration. The method combines the simulation of the path rerouting algorithm
with a “dynamic path failure importance sampling” (DPFS) scheme to estimate
path availabilities efficiently.
In DPFS, the failure rates of network elements are biased at increased rates until
path failures are observed under rerouting. The simulated model uses “failure
equivalence groups,” with finite/infinite sources of failure events and finite/infinite
pools of repair personnel, to facilitate the modeling of bi-directional link failures,
and more general geographically distributed failure scenarios.
The analysis of a large mesh network example demonstrates the practicality of
the technique.

INDEX TERMS
Availability, biasing, failure, importance, mesh, model, network, path, restoration,
risk, sampling, simulation.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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IEEE/ACM TRANSACTIONS ON NETWORKING, FEBRUARY 2011

EFFICIENT MULTIPATH COMMUNICATION FOR
TIME-CRITICAL APPLICATIONS IN
UNDERWATER ACOUSTIC SENSOR NETWORKS

ABSTRACT
Due to the long propagation delay and high error rate of acoustic channels, it is
very challenging to provide reliable data transfer for time-critical applications in
an energy-efficient way. On the one hand, traditional retransmission upon failure
usually introduces very large end-to-end delay and is thus not proper for time-
critical services.
On the other hand, common approaches without retransmission consume lots of
energy. In this paper, we propose a new multipath power-control transmission
(MPT) scheme, which can guarantee certain end-to-end packet error rate while
achieving a good balance between the overall energy efficiency and the end-to-
end packet delay.
MPT smartly combines power control with multipath routing and packet combining
at the destination. With carefully designed power-control strategies, MPT
consumes much less energy than the conventional one-path transmission
scheme without retransmission.
Besides, since no hop-by-hop retransmission is allowed, MPT introduces much
shorter delays than the traditional one-path scheme with retransmission. We
conduct extensive simulations to evaluate the performance of MPT. Our results
show that MPT is highly energy-efficient with low end-to-end packet delays.

INDEX TERMS
Applications, energy efficiency, network communications, underwater sensor
networks.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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IEEE/ACM TRANSACTIONS ON NETWORKING, APRIL 2011

ENERGY-EFFICIENT PROTOCOL
FOR COOPERATIVE NETWORKS

ABSTRACT
In cooperative networks, transmitting and receiving nodes recruit neighboring
nodes to assist in communication. We model a cooperative transmission link in
wireless networks as a transmitter cluster and a receiver cluster.
We then propose a cooperative communication protocol for establishment of
these clusters and for cooperative transmission of data. We derive the upper
bound of the capacity of the protocol, and we analyze the end-to-end robustness
of the protocol to data-packet loss, along with the tradeoff between energy
consumption and error rate.
The analysis results are used to compare the energy savings and the end-to-end
robustness of our protocol with two non-cooperative schemes, as well as to
another cooperative protocol published in the technical literature. The comparison
results show that, when nodes are positioned on a grid, there is a reduction in the
probability of packet delivery failure by two orders of magnitude for the values of
parameters considered.
Up to 80% in energy savings can be achieved for a grid topology, while for
random node placement our cooperative protocol can save up to 40% in energy
consumption relative to the other protocols. The reduction in error rate and the
energy savings translate into increased lifetime of cooperative sensor networks.

INDEX TERMS
Clustering, cooperative networks        energy-efficient   protocols,   cooperative
transmission, sensor networks.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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IEEE/ACM TRANSACTIONS ON NETWORKING, FEBRUARY 2011

DELAY ANALYSIS AND OPTIMALITY OF SCHEDULING
POLICIES FOR MULTIHOP WIRELESS NETWORKS

ABSTRACT
We analyze the delay performance of a multihop wireless network with axed route
between each source–destination pair. We develop a new queue grouping
technique to handle the complex correlations of the service process resulting
from the multihop nature of the rows. A general set-based interference model is
assumed that imposes constraints on links that can be served simultaneously at
any given time. These interference constraints are used to obtain a fundamental
lower bound on the delay performance of any scheduling policy for the system.
We present a systematic methodology to derive such lower bounds. For a special
wireless system, namely the clique, we design a policy that is sample-path delay-
optimal. For the tandem queue network, where the delay-optimal policy is known,
the expected delay of the optimal policy numerically coincides with the lower
bound. We conduct extensive numerical studies to suggest that the average
delay of the back-pressure scheduling policy can be made close to the lower
bound by using appropriate functions of queue length.

INDEX TERMS
Delay, dynamic control, low control, Lyapunov analysis, Markov chains,
optimization, queueing analysis, scheduling, wireless mesh network.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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IEEE/ACM TRANSACTIONS ON NETWORKING, FEBRUARY 2011

CROSSTALK-PREVENTING SCHEDULING IN SINGLE-AND
TWO-STAGE AWG-BASED CELL SWITCHES

ABSTRACT
Array waveguide grating (AWG)-based optical switching fabrics are receiving
increasing attention due to their simplicity and good performance. However,
AWGs are affected by coherent crosstalk that can significantly impair system
operation when the same wavelength is used simultaneously on several input
ports.
To permit large port counts in a AWG, a possible solution is to schedule data
transmissions across the AWG preventing switch configurations that generate
large crosstalk. We study the properties and the existence conditions of switch
configurations able to control coherent crosstalk.
The presented results show that, by running a properly constrained scheduling
algorithm to avoid or minimize crosstalk, it is possible to operate an AWG-based
switch with large port counts without significant performance degradation.

INDEX TERMS
Arrayed waveguide grating (AWG), coherent crosstalk, input-queued switches,
optical switchings, scheduling algorithms.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE/ACM TRANSACTIONS ON NETWORKING, FEBRUARY 2011

JAMMING-AWARE TRAFFIC ALLOCATION FOR
MULTIPLE-PATH ROUTING USING PORTFOLIO
SELECTION

ABSTRACT
Multiple-path source routing protocols allow a data source node to distribute the
total traffic among available paths. In this paper, we consider the problem of
jamming-aware source routing in which the source node performs traffic
allocation based on empirical jamming statistics at individual network nodes.
We formulate this traffic allocation as a lossy network flow optimization problem
using portfolio selection theory from financial statistics.
We show that in multisource networks, this centralized optimization problem can
be solved using a distributed algorithm based on decomposition in network utility
maximization (NUM).
We demonstrate the network’s ability to estimate the impact of jamming and
incorporate these estimates into the traffic allocation problem. Finally, we
simulate the achievable throughput using our proposed traffic allocation method
in several scenarios.

INDEX TERMS
Jamming, multiple-path routing, network utility maximization (NUM), optimization,
portfolio selection theory.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE/ACM TRANSACTIONS ON NETWORKING, FEBRUARY 2011

CONTINUOUS NEIGHBOR DISCOVERY IN
ASYNCHRONOUS SENSOR NETWORKS

ABSTRACT
In most sensor networks, the nodes are static. Nevertheless, node connectivity is
subject to changes because of disruptions in wireless communication,
transmission power changes, or loss of synchronization between neighboring
nodes.
Hence, even after a sensor is aware of its immediate neighbors, it must
continuously maintain its view, a process we call continuous neighbor discovery.
In this work, we distinguish between neighbor discovery during sensor network
initialization and continuous neighbor discovery. We focus on the latter and view
it as a joint task of all the nodes in every connected segment.
Each sensor employs a simple protocol in a coordinate effort to reduce power
consumption without increasing the time required to detect hidden sensors.

INDEX TERMS
Neighbor discovery, sensor networks.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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IEEE/ACM TRANSACTIONS ON NETWORKING, FEBRUARY 2011

DIVISION MULTIPLEXING

ABSTRACT
A number of commercial peer-to-peer (P2P) systems for live streaming have
been introduced in recent years. The behavior of these popular systems has
been extensively studied in several measurement papers.
Due to the proprietary nature of these commercial systems, however, these
studies have to rely on a “black-box” approach, where packet traces are collected
from a single or a limited number of measurement points, to infer various
properties of traf?c on the control and data planes.
Although such studies are useful to compare different systems from the end-
user’s perspective, it is dif?cult to intuitively understand the observed properties
without fully reverse-engineering the under-lying systems. In this paper, we
describe the network architecture of Zattoo, one of the largest production live
streaming providers in Europe at the time of writing, and present a large-scale
mea- surement study of Zattoo using data collected by the provider.
To highlight, we found that even when the Zattoo system was heavily loaded with
as high as 20 000 concurrent users on a single overlay, the median channel join
delay remained less than 2–5 s, and that, for a majority of users, the streamed
signal lags over-the-air broadcast signal by no more than 3 s.

Index Terms
Live streaming, network architecture, peer-to-peer (P2P) system.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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IEEE/ACM TRANSACTIONS ON NETWORKING, FEBRUARY 2011

TOPOLOGICAL TRANSFORMATION APPROACHES TO
TCAM-BASED PACKET CLASSIFICATION

ABSTRACT
Several range reencoding schemes have been pro-posed to mitigate the effect of
range expansion and the limitations of small capacity, large power consumption,
and high heat generation of ternary content addressable memory (TCAM)-based
packet classification systems.
However, they all disregard the semantics of classifiers and therefore miss
significant opportunities for space compression. In this paper, we propose new
approaches to range reencoding by taking into account classifier semantics.
Fundamentally different from prior work, we view reencoding as a topological
transformation process from one colored hyperrect- angle to another, where the
color is the decision associated with a given packet. Stated another way, we
reencode the entire classifier by considering the classifier’s decisions rather than
reencode only ranges in the classifier ignoring the classifier’s decisions as prior
work does.
We present two orthogonal, yet composable, reen-coding approaches: domain
compression and prefix alignment. Our techniques significantly outperform all
previous reencoding techniques.
In comparison to prior art, our experimental results show that our techniques
achieve at least five times more space reduction in terms of TCAM space for an
encoded classifier and at least three times more space reduction in terms of
TCAM space for a reencoded classifier and its transformers. This, in turn, leads
to improved throughput and decreased power consumption.

Index Terms
Hardware-based packet classification,        range   en-coding,   ternary   content

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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CLOUD COMPUTING

PERFORMANCE ANALYSIS OF CLOUD COMPUTING
Parallel and Distributed Systems, IEEE Transactions June 2011

ABSTRACT
Cloud computing is an emerging commercial infrastructure paradigm that
promises to eliminate the need for maintaining expensive computing facilities by
companies and institutes alike. Through the use of virtualization and resource
time sharing, clouds serve with a single set of physical resources a large user
base with different needs.
Thus, clouds have the potential to provide to their owners the benefits of an
economy of scale and, at the same time, become an alternative for scientists to
clusters, grids, and parallel production environments. However, the current
commercial clouds have been built to support web and small database workloads,
which are very different from typical scientific computing workloads.
Moreover, the use of virtualization and resource time-sharing may introduce
significant performance penalties for the demanding scientific computing
workloads. In this work, we analyze the performance of cloud computing services
for scientific computing workloads. We quantify the presence in real scientific
computing workloads of Many-Task Computing (MTC) users, that is, of users who
employ loosely coupled applications comprising many tasks to achieve their
scientific goals.
Then, we perform an empirical evaluation of the performance of four commercial
cloud computing services including Amazon EC2, which is currently the largest
commercial cloud. Last, we compare through trace-based simulation the
performance characteristics and cost models of clouds and other scientific
computing platforms, for general and MTC-based scientific computing workloads.
Our results indicate that the current clouds need an order of magnitude in
performance improvement to be useful to the scientific community, and show
which improvements should be considered first to address this discrepancy
between offer and demand.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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CLOUD COMPUTING

EXPLOITING DYNAMIC RESOURCE ALLOCATION FOR
EFFICIENT PARALLEL DATA PROCESSING IN THE CLOUD
Parallel and Distributed Systems, IEEE Transactions June 2011

In recent years ad hoc parallel data processing has emerged to be one of the
killer applications for Infrastructure-as-a-Service (IaaS) clouds. Major Cloud
computing companies have started to integrate frameworks for parallel data
processing in their product portfolio, making it easy for customers to access
these services and to deploy their programs.
However, the processing frameworks which are currently used have been
designed for static, homogeneous cluster setups and disregard the particular
nature of a cloud. Consequently, the allocated compute resources may be
inadequate for big parts of the submitted job and unnecessarily increase
processing time and cost.
In this paper, we discuss the opportunities and challenges for efficient parallel
data processing in clouds and present our research project Nephele. Nephele is
the first data processing framework to explicitly exploit the dynamic resource
allocation offered by today's IaaS clouds for both, task scheduling and execution.
Particular tasks of a processing job can be assigned to different types of virtual
machines which are automatically instantiated and terminated during the job
execution. Based on this new framework, we perform extended evaluations of
MapReduce-inspired processing jobs on an IaaS cloud system and compare the
results to the popular data processing framework Hadoop.

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SIGMATREE SOLUTIONS                               IEEE PROJECTS 2011-12
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CLOUD COMPUTING

ENABLING PUBLIC AUDITABILITY AND DATA DYNAMICS
FOR STORAGE SECURITY IN CLOUD COMPUTING
Parallel and Distributed Systems, IEEE Transactions May 2011

ABSTRACT
Cloud Computing has been envisioned as the next-generation architecture of IT Enterprise. It
moves the application software and databases to the centralized large data centers, where the
management of the data and services may not be fully trustworthy.
This unique paradigm brings about many new security challenges, which have not been well
understood. This work studies the problem of ensuring the integrity of data storage in Cloud
Computing. In particular, we consider the task of allowing a third party auditor (TPA), on behalf
of the cloud client, to verify the integrity of the dynamic data stored in the cloud.
The introduction of TPA eliminates the involvement of the client through the auditing of whether
his data stored in the cloud are indeed intact, which can be important in achieving economies of
scale for Cloud Computing.
The support for data dynamics via the most general forms of data operation, such as block
modification, insertion, and deletion, is also a significant step toward practicality, since services
in Cloud Computing are not limited to archive or backup data only. While prior works on ensuring
remote data integrity often lacks the support of either public auditability or dynamic data
operations, this paper achieves both.
We first identify the difficulties and potential security problems of direct extensions with fully
dynamic data updates from prior works and then show how to construct an elegant verification
scheme for the seamless integration of these two salient features in our protocol design. In
particular, to achieve efficient data dynamics, we improve the existing proof of storage models
by manipulating the classic Merkle Hash Tree construction for block tag authentication.
To support efficient handling of multiple auditing tasks, we further explore the technique of
bilinear aggregate signature to extend our main result into a multiuser setting, where TPA can
perform multiple auditing tasks simultaneously. Extensive security and performance analysis
show that the proposed schemes are highly efficient and provably secure.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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CLOUD COMPUTING

HEURISTICS BASED QUERY PROCESSING FOR LARGE
RDF GRAPHS USING CLOUD COMPUTING
Knowledge and Data Engineering, IEEE Transactions on

ABSTRACT
Semantic Web is an emerging area to augment human reasoning for which
various technologies are being developed. These technologies have been
standardized by W3C.
One such standard is the RDF. With the explosion of semantic web technologies,
large RDF graphs are common place. Current frameworks do not scale for large
RDF graphs and as a result does not address these challenges. In this paper, we
describe a framework that we built using Hadoop to store and retrieve large
numbers of RDF triples by exploiting the cloud computing paradigm.
We describe a scheme to store RDF data in Hadoop Distributed File System.
More than one Hadoop job may be needed to answer a query because a triple
pattern in a query cannot take part in more than one join in a Hadoop job.
To determine the jobs, we present an algorithm to generate query plan, whose
worst case cost is bounded, based on a greedy approach to answer a SPARQL
Our results show that we can store large RDF graphs in Hadoop clusters built
with cheap commodity class hardware. Furthermore, we show that our framework
is scalable and efficient and can handle large amounts of RDF data, unlike

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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CLOUD COMPUTING
OPTIMIZATION OF RESOURCE PROVISIONING COST IN
CLOUD COMPUTING
IEEE Transactions on Services Computing
ABSTRACT
In cloud computing, cloud providers can offer cloud consumers two provisioning
plans for computing resources, namely reservation and on-demand plans. In
general, cost of utilizing computing resources provisioned by reservation plan is
cheaper than that provisioned by on-demand plan, since cloud consumer has to
With the reservation plan, the consumer can reduce the total resource
provisioning cost. However, the best advance reservation of resources is difficult
to be achieved due to uncertainty of consumer’s future demand and providers’
resource prices.
To address this problem, an optimal cloud resource provisioning (OCRP)
algorithm is proposed by formulating a stochastic programming model. The
OCRP algorithm can provision computing resources for being used in multiple
provisioning stages as well as a long-term plan, e.g., four stages in a quarter plan
and twelve stages in a yearly plan. The demand and price uncertainty is
considered in OCRP.
In this paper, different approaches to obtain the solution of OCRP algorithm are
considered including deterministic equivalent formulation, sample-average
approximation, and Benders decomposition. Numerical studies are extensively
performed in which the results clearly show that with the OCRP algorithm, cloud
consumer can successfully minimize total cost of resource provisioning in cloud
computing environments.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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CLOUD COMPUTING

TOWARDS SECURE AND DEPENDABLE STORAGE
SERVICES IN CLOUD COMPUTING
Services Computing, IEEE Transactions on
ABSTRACT
As one of the emerging services in cloud paradigm, cloud storage enables users
to remotely store their data into the cloud so as to enjoy the on-demand high
quality applications and services from a shared pool of configurable computing
resources.
While cloud storage relieves users from the burden of local storage management
and maintenance, it is also relinquishing users&#8217; ultimate control over the
fate of their data, which may put the correctness of outsourced data into risks.
In order to regain the assurances of cloud data integrity and availability and
enforce the quality of cloud storage service for users, we propose a highly
efficient and flexible distributed storage verification scheme with two salient
features, opposing to its predecessors.
By utilizing the homomorphic token with distributed erasure-coded data, our
scheme achieves the integration of storage correctness insurance and data error
localization, i.e., the identification of misbehaving server(s).
Unlike most prior works, the new scheme further supports secure and efficient
dynamic operations on outsourced data, including: block modification, deletion
and append. Extensive security and performance analysis shows the proposed
scheme is highly efficient and resilient against Byzantine failure, malicious data
modification attack, and even server colluding attacks.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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CLOUD COMPUTING

CLOUDTPS: SCALABLE TRANSACTIONS FOR WEB
APPLICATIONS IN THE CLOUD
Services Computing, IEEE Transactions on

ABSTRACT
NoSQL Cloud data stores provide scalability and high availability properties for
web applications, but at the same time they sacrifice data consistency. However,
many applications cannot afford any data inconsistency.
CloudTPS is a scalable transaction manager, which guarantees full ACID
properties for multi-item transactions issued by Web applications, even in the
presence of server failures and network partitions.
We implement this approach on top of the two main families of scalable data
layers: Bigtable and SimpleDB. Performance evaluation on top of HBase (an
open-source version of Bigtable) in our local cluster and Amazon SimpleDB in the
Amazon cloud shows that our system scales linearly at least up to 40 nodes in
our local cluster and 80 nodes in the Amazon cloud.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
Promise for the Best Projects
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MINING CLUSTER-BASED TEMPORAL
MOBILE SEQUENTIAL PATTERNS IN
LOCATION-BASED SERVICE ENVIRONMENTS
Knowledge and Data Engineering, IEEE Transactions June 2011

ABSTRACT
Researches on Location-Based Service (LBS) have been emerging in recent
years due to a wide range of potential applications. One of the active topics is the
mining and prediction of mobile movements and associated transactions. Most of
existing studies focus on discovering mobile patterns from the whole logs.
However, this kind of patterns may not be precise enough for predictions since
the differentiated mobile behaviors among users and temporal periods are not
considered. In this paper, we propose a novel algorithm, namely, Cluster-based
Temporal Mobile Sequential Pattern Mine (CTMSP-Mine), to discover the Cluster-
based Temporal Mobile Sequential Patterns (CTMSPs). Moreover, a prediction
strategy is proposed to predict the subsequent mobile behaviors.
In CTMSP-Mine, user clusters are constructed by a novel algorithm named
Cluster-Object-based Smart Cluster Affinity Search Technique (CO-Smart-CAST)
and similarities between users are evaluated by the proposed measure, Location-
Based Service Alignment (LBS-Alignment).
Meanwhile, a time segmentation approach is presented to find segmenting time
intervals where similar mobile characteristics exist. To our best knowledge, this is
the first work on mining and prediction of mobile behaviors with considerations of
user relations and temporal property simultaneously. Through experimental
evaluation under various simulated conditions, the proposed methods are shown
to deliver excellent performance.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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COSDES: A COLLABORATIVE SPAM DETECTION
SYSTEM WITH A NOVEL E-MAIL ABSTRACTION SCHEME
Knowledge and Data Engineering, IEEE Transactions May 2011

ABSTRACT
E-mail communication is indispensable nowadays, but the e-mail spam problem
continues growing drastically. In recent years, the notion of collaborative spam
filtering with near-duplicate similarity matching scheme has been widely
discussed.
The primary idea of the similarity matching scheme for spam detection is to
maintain a known spam database, formed by user feedback, to block subsequent
near-duplicate spams.
On purpose of achieving efficient similarity matching and reducing storage
utilization, prior works mainly represent each e-mail by a succinct Abstraction
derived from e-mail content text. However, these Abstractions of e-mails cannot
fully catch the evolving nature of spams, and are thus not effective enough in
near-duplicate detection.
In this paper, we propose a novel e-mail Abstraction scheme, which considers e-
mail layout structure to represent e-mails. We present a procedure to generate
the e-mail Abstraction using HTML content in e-mail, and this newly devised
Abstraction can more effectively capture the near-duplicate phenomenon of
spams.
Moreover, we design a complete spam detection system Cosdes (standing for
COllaborative Spam DEtection System), which possesses an efficient near-
duplicate matching scheme and a progressive update scheme.
The progressive update scheme enables system Cosdes to keep the most up-to-
date information for near-duplicate detection. We evaluate Cosdes on a live data
set collected from a real e-mail server and show that our system outperforms the
prior approaches in detection results and is applicable to the real world.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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A LINK ANALYSIS EXTENSION OF CORRESPONDENCE
ANALYSIS FOR MINING RELATIONAL DATABASES
Knowledge and Data Engineering, IEEE Transactions April 2011

ABSTRACT
This work introduces a link analysis procedure for discovering relationships in a
relational database or a graph, generalizing both simple and multiple
correspondence analysis. It is based on a random walk model through the
database defining a Markov chain having as many states as elements in the
database.
Suppose we are interested in analyzing the relationships between some elements
(or records) contained in two different tables of the relational database. To this
end, in a first step, a reduced, much smaller, Markov chain containing only the
elements of interest and preserving the main characteristics of the initial chain, is
extracted by stochastic complementation.
This reduced chain is then analyzed by projecting jointly the elements of interest
in the diffusion map subspace and visualizing the results. This two-step
procedure reduces to simple correspondence analysis when only two tables are
defined, and to multiple correspondence analysis when the database takes the
form of a simple star-schema.
On the other hand, a kernel version of the diffusion map distance, generalizing
the basic diffusion map distance to directed graphs, is also introduced and the
links with spectral clustering are discussed. Several data sets are analyzed by
using the proposed methodology, showing the usefulness of the technique for
extracting relationships in relational databases or graphs.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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A PERSONALIZED ONTOLOGY MODEL FOR WEB
INFORMATION GATHERING
Knowledge and Data Engineering, IEEE Transactions on April 2011

ABSTRACT
As a model for knowledge description and formalization, ontologies are widely
used to represent user profiles in personalized web information gathering.
However, when representing user profiles, many models have utilized only
knowledge from either a global knowledge base or a user local information. In
this paper, a personalized ontology model is proposed for knowledge
representation and reasoning over user profiles.
This model learns ontological user profiles from both a world knowledge base and
user local instance repositories. The ontology model is evaluated by comparing it
against benchmark models in web information gathering. The results show that
this ontology model is successful.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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A MACHINE LEARNING APPROACH FOR IDENTIFYING
DISEASE-TREATMENT RELATIONS IN SHORT TEXTS
Knowledge and Data Engineering, IEEE Transactions June 2011

ABSTRACT
The Machine Learning (ML) field has gained its momentum in almost any domain
of research and just recently has become a reliable tool in the medical domain.
The empirical domain of automatic learning is used in tasks such as medical
decision support, medical imaging, protein-protein interaction, extraction of
medical knowledge, and for overall patient management care.
ML is envisioned as a tool by which computer-based systems can be integrated in
the healthcare field in order to get a better, more efficient medical care. This
paper describes a ML-based methodology for building an application that is
capable of identifying and disseminating healthcare information.
It extracts sentences from published medical papers that mention diseases and
treatments, and identifies semantic relations that exist between diseases and
treatments.
Our evaluation results for these tasks show that the proposed methodology
obtains reliable outcomes that could be integrated in an application to be used in
the medical care domain. The potential value of this paper stands in the ML
settings that we propose and in the fact that we outperform previous results on
the same data set.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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DESIGN AND IMPLEMENTATION OF AN INTRUSION
RESPONSE SYSTEM FOR RELATIONAL DATABASES
Knowledge and Data Engineering, IEEE Transactions June 2011

ABSTRACT
The intrusion response component of an overall intrusion detection system is
responsible for issuing a suitable response to an anomalous request. We propose
the notion of database response policies to support our intrusion response
system tailored for a DBMS.
Our interactive response policy language makes it very easy for the database
administrators to specify appropriate response actions for different circumstances
depending upon the nature of the anomalous request. The two main issues that
we address in context of such response policies are that of policy matching, and
For the policy matching problem, we propose two algorithms that efficiently
search the policy database for policies that match an anomalous request. We
also extend the PostgreSQL DBMS with our policy matching mechanism, and
report experimental results. The experimental evaluation shows that our
techniques are very efficient.
The other issue that we address is that of administration of response policies to
prevent malicious modifications to policy objects from legitimate users. We
propose a novel Joint Threshold Administration Model (JTAM) that is based on
the principle of separation of duty.
The key idea in JTAM is that a policy object is jointly administered by at least k
database administrator (DBAs), that is, any modification made to a policy object
will be invalid unless it has been authorized by at least k DBAs.
We present design details of JTAM which is based on a cryptographic threshold
signature scheme, and show how JTAM prevents malicious modifications to
policy objects from authorized users. We also implement JTAM in the
PostgreSQL DBMS, and report experimental results on the efficiency of our
techniques.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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CLASSIFICATION AND NOVEL CLASS DETECTION IN
CONCEPT-DRIFTING DATA STREAMS UNDER TIME
CONSTRAINTS
Knowledge and Data Engineering, IEEE Transactions June 2011

ABSTRACT
Most existing data stream classification techniques ignore one important aspect
of stream data: arrival of a novel class. We address this issue and propose a data
stream classification technique that integrates a novel class detection mechanism
into traditional classifiers, enabling automatic detection of novel classes before
the true labels of the novel class instances arrive.
Novel class detection problem becomes more challenging in the presence of
concept-drift, when the underlying data distributions evolve in streams. In order to
determine whether an instance belongs to a novel class, the classification model
sometimes needs to wait for more test instances to discover similarities among
those instances.
A maximum allowable wait time Tc is imposed as a time constraint to classify a
test instance. Furthermore, most existing stream classification approaches
assume that the true label of a data point can be accessed immediately after the
data point is classified.
In reality, a time delay Tl is involved in obtaining the true label of a data point
since manual labeling is time consuming. We show how to make fast and correct
classification decisions under these constraints and apply them to real
benchmark data. Comparison with state-of-the-art stream classification
techniques prove the superiority of our approach.

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SIGMATREE SOLUTIONS                         IEEE PROJECTS 2011-12
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ANOMALY DETECTION IN NETWORK TRAFFIC BASED ON
STATISTICAL INFERENCE AND ALPHA-STABLE MODELING
Dependable and Secure Computing, IEEE Transactions: July-Aug. 2011

ABSTRACT
This paper proposes a novel method to detect anomalies in network traffic, based
on a nonrestricted α-stable first-order model and statistical hypothesis testing. To
this end, we give statistical evidence that the marginal distribution of real traffic is
adequately modeled with α-stable functions and classify traffic patterns by means
of a Generalized Likelihood Ratio Test (GLRT).
The method automatically chooses traffic windows used as a reference, which the
traffic window under test is compared with, with no expert intervention needed to
that end. We focus on detecting two anomaly types, namely floods and flash-
crowds, which have been frequently studied in the literature.
Performance of our detection method has been measured through Receiver
Operating Characteristic (ROC) curves and results indicate that our method
outperforms the closely-related state-of-the-art contribution described in.
All experiments use traffic data collected from two routers at our university-a
25,000 students institution-which provide two different levels of traffic
aggregation for our tests (traffic at a particular school and the whole university).
In addition, the traffic model is tested with publicly available traffic traces. Due to
the complexity of α-stable distributions, care has been taken in designing
appropriate numerical algorithms to deal with the model.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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ELMO: ENERGY AWARE LOCAL MONITORING IN
SENSOR NETWORKS
Dependable and Secure Computing, IEEE Transactions: July-Aug. 2011

ABSTRACT
Over the past decade, local monitoring has been shown to be a powerful
technique for improving security in multihop wireless sensor networks (WSNs).
Indeed, local monitoring-based security algorithms are becoming the most
popular tool for providing security in WSNs.
However, local monitoring as it is currently practiced is costly in terms of energy
consumption, a major drawback for energy-constrained systems such as WSNs.
In WSN environments, the scarce power resources are typically addressed
through sleep-wake scheduling of the nodes.
However, sleep-wake scheduling techniques in WSNs are vulnerable even to
simple attacks. In this paper, a new technique is proposed that promises to allow
operation of WSNs in a manner that is both energy-efficient and secure. The
proposed technique combines local monitoring with a novel, more secure form of
sleep-wake scheduling.
The latter is a new methodology dubbed Elmo (Energy Aware Local MOnitoring in
Sensor Networks), which enables sleep-wake management in a secure manner
even in the face of adversarial nodes that choose not to awaken nodes
responsible for monitoring their traffic.
An analytical proof is given showing that security coverage is not weakened
under Elmo. Moreover, ns-2 simulation results show that the performance of local
monitoring is practically unchanged, while energy savings of 20 to 100 times are
achieved, depending on the scenario.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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EFFICIENT FAULT DETECTION AND DIAGNOSIS IN
COMPLEX SOFTWARE SYSTEMS WITH INFORMATION-
THEORETIC MONITORING
Dependable and Secure Computing, IEEE Transactions on

ABSTRACT
Management metrics of complex software systems exhibit stable correlations
which can enable fault detection and diagnosis. Current approaches use specific
analytic forms, typically linear, for modeling correlations. In practice, more
complex nonlinear relationships exist between metrics. Moreover, most
intermetric correlations form clusters rather than simple pairwise correlations.
These clusters provide additional information and offer the possibility for
optimization. In this paper, we address these issues by using Normalized Mutual
Information (NMI) as a similarity measure to identify clusters of correlated
metrics, without assuming any specific form for the metric relationships. We show
how to apply the Wilcoxon Rank-Sum test on the entropy measures to detect
errors in the system.
We also present three diagnosis algorithms to locate faulty components:
RatioScore, based on the Jaccard coefficient, SigScore, which incorporates
knowledge of component dependencies, and BayesianScore, which uses
Bayesian inference to assign a fault probability to each component.
We evaluate our approach in the context of a complex enterprise application, and
show that 1) stable, nonlinear correlations exist and can be captured with our
approach; 2) we can detect a large fraction of faults with a low false positive rate
(we detect up to 18 of the 22 faults we injected); and 3) we improve the diagnosis
with our new diagnosis algorithms.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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CONFIDENTIAL DATABASES
Dependable and Secure Computing, IEEE Transactions on
Issue Date: July-Aug. 2011

ABSTRACT
Suppose Alice owns a k-anonymous database and needs to determine whether
her database, when inserted with a tuple owned by Bob, is still k-anonymous.
Also, suppose that access to the database is strictly controlled, because for
example data are used for certain experiments that need to be maintained
confidential.
Clearly, allowing Alice to directly read the contents of the tuple breaks the privacy
of Bob (e.g., a patient's medical record); on the other hand, the confidentiality of
the database managed by Alice is violated once Bob has access to the contents
of the database.
Thus, the problem is to check whether the database inserted with the tuple is still
k-anonymous, without letting Alice and Bob know the contents of the tuple and
the database, respectively. In this paper, we propose two protocols solving this
problem on suppression-based and generalization-based k-anonymous and
confidential databases.
The protocols rely on well-known cryptographic assumptions, and we provide
theoretical analyses to proof their soundness and experimental results to
illustrate their efficiency.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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DYNAMICS OF MALWARE SPREAD IN DECENTRALIZED
PEER-TO-PEER NETWORKS
Dependable and Secure Computing, IEEE Transactions: July-Aug. 2011

ABSTRACT
In this paper, we formulate an analytical model to characterize the spread of
malware in decentralized, Gnutella type peer-to-peer (P2P) networks and study
the dynamics associated with the spread of malware. Using a compartmental
model, we derive the system parameters or network conditions under which the
P2P network may reach a malware free equilibrium.
The model also evaluates the effect of control strategies like node quarantine on
stifling the spread of malware. The model is then extended to consider the impact
of P2P networks on the malware spread in networks of smart cell phones.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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LOW-ENERGY SYMMETRIC KEY DISTRIBUTION IN
WIRELESS SENSOR NETWORKS
Dependable and Secure Computing, IEEE Transactions on Issue Date: May-
June 2011

ABSTRACT
In this work, a scheme for key distribution and network access in a Wireless
Sensor Network (WSN) that utilizes Identity-Based Cryptography (IBC) is
presented.
The scheme is analyzed on the ARM920T processor and measurements were
taken for the runtime and energy of its components. It was found that the Tate
pairing component of the scheme consumes significant amounts of energy, and
so should be ported to hardware.
An accelerator was implemented in 65 nm Complementary Metal Oxide Silicon
(CMOS) technology and area, timing, and energy figures have been obtained for
the design. Results indicate that a hardware implementation of IBC would meet
the strict energy constraint required of a wireless sensor network node.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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REPLICA PLACEMENT FOR ROUTE DIVERSITY IN
TREE-BASED ROUTING DISTRIBUTED HASH TABLES
Dependable and Secure Computing, IEEE Transactions on Issue Date: May-
June 2011

ABSTRACT
Distributed hash tables (DHTs) share storage and routing responsibility among all
nodes in a peer-to-peer network. These networks have bounded path length
misroute lookups.
We address both of these problems through replica placement. We characterize
tree-based routing DHTs and define MaxDisjoint, a replica placement that creates
route diversity for these DHTs. We prove that this placement creates disjoint
routes and find the replication degree necessary to produce a desired number of
disjoint routes.
Using simulations of Pastry (a tree-based routing DHT), we evaluate the impact
of MaxDisjoint on routing robustness compared to other placements when nodes
are compromised at random or in a contiguous run.
Furthermore, we consider another route diversity mechanism that we call
neighbor set routing and show that, when used with our replica placement, it can
successfully route messages to a correct replica even with a quarter of the nodes
in the system compromised at random.
Finally, we demonstrate a family of replica query strategies that can trade off
response time and system load. We present a hybrid query strategy that keeps
response time low without producing too high a load.

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SIGMATREE SOLUTIONS                               IEEE PROJECTS 2011-12
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ROBUST CORRELATION OF ENCRYPTED ATTACK TRAFFIC
THROUGH STEPPING STONES BY FLOW WATERMARKING
Dependable and Secure Computing, IEEE Transactions May-June 2011

ABSTRACT
Network-based intruders seldom attack their victims directly from their own computer. Often,
they stage their attacks through intermediate “stepping stones” in order to conceal their identity
and origin. To identify the source of the attack behind the stepping stone(s), it is necessary to
correlate the incoming and outgoing flows or connections of a stepping stone.
To resist attempts at correlation, the attacker may encrypt or otherwise manipulate the
connection traffic. Timing-based correlation approaches have been shown to be quite effective
in correlating encrypted connections. However, timing-based correlation approaches are subject
to timing perturbations that may be deliberately introduced by the attacker at stepping stones.
In this paper, we propose a novel watermark-based-correlation scheme that is designed
specifically to be robust against timing perturbations. Unlike most previous timing-based
correlation approaches, our watermark-based approach is “active” in that it embeds a unique
watermark into the encrypted flows by slightly adjusting the timing of selected packets.
The unique watermark that is embedded in the encrypted flow gives us a number of advantages
over passive timing-based correlation in resisting timing perturbations by the attacker. In
contrast to the existing passive correlation approaches, our active watermark-based correlation
does not make any limiting assumptions about the distribution or random process of the original
interpacket timing of the packet flow.
In theory, our watermark-based correlation can achieve arbitrarily close to 100 percent
correlation true positive rate (TPR), and arbitrarily close to 0 percent false positive rate (FPR) at
the same time for sufficiently long flows, despite arbitrarily large (but bounded) timing
perturbations of any distribution by the attacker.
Our paper is the first that identifies 1) accurate quantitative tradeoffs between the achievable
correlation effectiveness a- - nd the defining characteristics of the timing perturbation; and 2) a
provable upper bound on the number of packets needed to achieve a desired correlation
effectiveness, given the amount of timing perturbation.
Experimental results show that our active watermark-based correlation performs better and
requires fewer packets than existing, passive timing-based correlation methods in the presence
of random timing perturbations.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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MEASUREMENT FOR NEXT GENERATION NETWORKS
Network and Service Management, IEEE Transactions on
Issue Date: March 2011

ABSTRACT
Internet performance measurement is commonly perceived as a high-cost
control-plane activity and until now it has tended to be implemented on top of the
network's forwarding operation. Consequently, measurement mechanisms have
effectiveness.
In this paper, we present the software implementation of an in-line measurement
mechanism that uses native structures of the Internet Protocol version 6 (IPv6)
stack to piggyback measurement information on data-carrying traffic as this is
routed between two points in the network.
We carefully examine the overhead associated with both the measurement
process and the measurement data, and we demonstrate that direct two-point
measurement has minimal impact on throughput and on system processing load.
The results of this paper show that adequately engineered measurement
mechanisms that exploit selective processing do not compromise the network's
forwarding efficiency, and can be deployed in an always-on manner to reveal the
true performance of network traffic over small timescales.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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ON THE IMPACT OF SECURITY PROTOCOLS ON THE
PERFORMANCE OF SNMP
Network and Service Management, IEEE Transactions March 2011

ABSTRACT
Since the early 1990s, there have been several attempts to secure the Simple
Network Management Protocol (SNMP). The third version of the protocol,
published as full standard in 2002, introduced the User-based Security Model
(USM), which comes with its own user and key-management infrastructure.
Since then, network operators have reported that deploying another user and key
management infrastructure to secure SNMP is expensive and a reason to not
deploy SNMPv3.
This paper describes how existing security protocols operating above the
transport layer and below application protocols can be used to secure SNMP.
infrastructures that are used for other network management interfaces and hence
their use can reduce the operational costs associated with securing SNMP.
Our main contribution is a detailed performance analysis of a prototype
implementation, comparing the performance of SNMPv3 over SSH, TLS, and
DTLS with other versions of SNMP. We also discuss the differences between the
various options to secure SNMP and provide guidelines for choosing solutions to
implement or deploy.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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LOCATING EQUIVALENT SERVANTS OVER P2P
NETWORKS
Network and Service Management, IEEE Transactions March 2011

ABSTRACT
While peer-to-peer networks are mainly used to locate unique resources across
the Internet, new interesting deployment scenarios are emerging. Particularly,
some applications (e.g., VoIP) are proposing the creation of overlays for the
localization of services based on equivalent servants (e.g., voice relays).
This paper explores the possible overlay architectures that can be adopted to
provide such services, showing how an unstructured solution based on a scale-
free overlay topology is an effective option to deploy in this context.
Consequently, we propose EQUATOR (EQUivalent servAnt locaTOR), an
unstructured overlay implementing the above mentioned operating principles,
based on an overlay construction algorithm that well approximates an ideal scale-
free construction model. We present both analytical and simulation results which
support our overlay topology selection and validate the proposed architecture.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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COOPERATIVE CHANNELIZATION IN WIRELESS
NETWORKS WITH NETWORK CODING
Parallel and Distributed Systems, IEEE Transactions July 2011

ABSTRACT
In this paper, we address congestion of multicast traffic in multihop wireless
networks through a combination of network coding and resource reservation.
Network coding reduces the number of transmissions required in multicast flows,
thus allowing a network to approach its multicast capacity. In addition, it
efficiently repairs errors in multicast flows by combining packets lost at different
destinations.
However, under conditions of extremely high congestion the repair capability of
network coding is seriously degraded. In this paper, we propose cooperative
channelization, in which portions of the transmission media are allocated to links
that are congested at the point where network coding cannot efficiently repair
loss. A health metric is proposed to allow comparison of need for channelization
Cooperative channelization considers the impact of channelization on overall
network performance before resource reservation is triggered. Our results show
that cooperative channelization improves overall network performance while
being well suited for wireless networks using network coding.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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THROUGHPUT OPTIMIZATION IN MULTIHOP WIRELESS
NETWORKS WITH MULTIPACKET RECEPTION AND
DIRECTIONAL ANTENNAS
Parallel and Distributed Systems, IEEE Transactions July 2011

ABSTRACT
Recent advances in the physical layer have enabled the simultaneous reception
of multiple packets by a node in wireless networks. We address the throughput
optimization problem in wireless networks that support multipacket reception
(MPR) capability. The problem is modeled as a joint routing and scheduling
problem, which is known to be NP-hard.
The scheduling subproblem deals with finding the optimal schedulable sets,
which are defined as subsets of links that can be scheduled or activated
simultaneously. We demonstrate that any solution of the scheduling subproblem
can be built with |E| + 1 or fewer schedulable sets, where |E| is the number of
This result is in contrast with previous works that stated that a solution of the
scheduling subproblem is composed of an exponential number of schedulable
sets. Due to the hardness of the problem, we propose a polynomial time scheme
based on a combination of linear programming and approximation algorithm
We illustrate the use of the scheme to study the impact of design parameters on
the performance of MPR-capable networks, including the number of transmit
interfaces, the beamwidth, and the receiver range of the antennas.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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ATTRIBUTE-BASED ACCESS CONTROL WITH EFFICIENT
REVOCATION IN DATA OUTSOURCING SYSTEMS
Parallel and Distributed Systems, IEEE Transactions on

ABSTRACT
Some of the most challenging issues in data outsourcing scenario are the
enforcement of authorization policies and the support of policy updates.
Ciphertext-policy attribute-based encryption is a promising cryptographic solution
to these issues for enforcing access control policies defined by a data owner on
outsourced data.
However, the problem of applying the attribute-based encryption in an outsourced
architecture introduces several challenges with regard to the attribute and user
revocation. In this paper, we propose an access control mechanism using
ciphertext-policy attribute-based encryption to enforce access control policies
with efficient attribute and user revocation capability.
The fine-grained access control can be achieved by dual encryption mechanism
which takes advantage of the attribute-based encryption and selective group key
distribution in each attribute group. We demonstrate how to apply the proposed
mechanism to securely manage the outsourced data.
The analysis results indicate that the proposed scheme is efficient and secure in
the data outsourcing systems.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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NETWORK IMMUNIZATION WITH DISTRIBUTED
AUTONOMY-ORIENTED ENTITIES
Parallel and Distributed Systems, IEEE Transactions July 2011

ABSTRACT
Many communication systems,         e.g., internet, can be modeled as complex
networks. For such networks,         immunization strategies are necessary for
preventing malicious attacks or      viruses being percolated from a node to its
neighboring nodes following their   connectivities.
In recent years, various immunization strategies have been proposed and
demonstrated, most of which rest on the assumptions that the strategies can be
executed in a centralized manner and/or that the complex network at hand is
reasonably stable (its topology will not change overtime).
In other words, it would be difficult to apply them in a decentralized network
environment, as often found in the real world. In this paper, we propose a
decentralized and scalable immunization strategy based on a self-organized
computing approach called autonomy-oriented computing (AOC) [1], [2]. In this
strategy, autonomous behavior-based entities are deployed in a decentralized
network, and are capable of collectively finding those nodes with high degrees of
Through experiments involving both synthetic and real-world networks, we
demonstrate that this strategy can effectively and efficiently locate highly-
connected nodes in decentralized complex network environments of various
topologies, and it is also scalable in handling large-scale decentralized networks.
We have compared our strategy with some of the well-known strategies, including
acquaintance and covering strategies on both synthetic and real-world networks.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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OPTIMIZATION OF RATE ALLOCATION WITH
DISTORTION GUARANTEE IN SENSOR NETWORKS
Parallel and Distributed Systems, IEEE Transactions on

Issue Date: July 2011
ABSTRACT
Lossy compression techniques are commonly used by long-term data-gathering
applications that attempt to identify trends or other interesting patterns in an
entire system since a data packet need not always be completely and
immediately transmitted to the sink. In these applications, a nonterminal sensor
node jointly encodes its own sensed data and the data received from its nearby
nodes.
The tendency for these nodes to have a high spatial correlation means that these
data packets can be efficiently compressed together using a rate-distortion
strategy. This paper addresses the optimal rate-distortion allocation problem,
which determines an optimal bit rate of each sensor based on the target overall
distortion to minimize the network transmission cost. We propose an analytically
optimal rate-distortion allocation scheme, and we also extend it to a distributed
version.
Based on the presented allocation schemes, a greedy heuristic algorithm is
proposed to build the most efficient data transmission structure to further reduce
the transmission cost.
The proposed methods were evaluated using simulations with real-world data
sets. The simulation results indicate that the optimal allocation strategy can
reduce the transmission cost to 6~15% of that for the uniform allocation scheme.

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A DATA THROUGHPUT PREDICTION AND OPTIMIZATION
COMPUTING
Parallel and Distributed Systems, IEEE Transactions June 2011

ABSTRACT
In this paper, we present the design and implementation of an application-layer
data throughput prediction and optimization service for many-task computing in
widely distributed environments. This service uses multiple parallel TCP streams
to improve the end-to-end throughput of data transfers.
A novel mathematical model is developed to determine the number of parallel
streams, required to achieve the best network performance. This model can
predict the optimal number of parallel streams with as few as three prediction
points. We implement this new service in the Stork Data Scheduler, where the
prediction points can be obtained using Iperf and GridFTP samplings.
Our results show that the prediction cost plus the optimized transfer time is much
less than the nonoptimized transfer time in most cases. As a result, Stork data
transfer jobs with optimization service can be completed much earlier, compared
to nonoptimized data transfer jobs.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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TOWARD EFFICIENT AND SIMPLIFIED DISTRIBUTED
DATA INTENSIVE COMPUTING
Parallel and Distributed Systems, IEEE Transactions June 2011

ABSTRACT
While the capability of computing systems has been increasing at Moore's Law,
the amount of digital data has been increasing even faster. There is a growing
need for systems that can manage and analyze very large data sets, preferably
on shared-nothing commodity systems due to their low expense.
In this paper, we describe the design and implementation of a distributed file
system called Sector and an associated programming framework called Sphere
that processes the data managed by Sector in parallel. Sphere is designed so
that the processing of data can be done in place over the data whenever
possible.
Sometimes, this is called data locality. We describe the directives Sphere
supports to improve data locality. In our experimental studies, the Sector/Sphere
system has consistently performed about 2-4 times faster than Hadoop, the most
popular system for processing very large data sets.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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NONLOCAL PDES-BASED MORPHOLOGY ON WEIGHTED
GRAPHS FOR IMAGE AND DATA PROCESSING
Image Processing, IEEE Transactions on Issue Date: June 2011

ABSTRACT
Mathematical morphology (MM) offers a wide range of operators to address
various image processing problems. These operators can be defined in terms of
algebraic (discrete) sets or as partial differential equations (PDEs). In this paper,
we introduce a nonlocal PDEs-based morphological framework defined on
weighted graphs.
We present and analyze a set of operators that leads to a family of discretized
morphological PDEs on weighted graphs. Our formulation introduces nonlocal
patch-based configurations for image processing and extends PDEs-based
approach to the processing of arbitrary data such as nonuniform high dimensional
data.
Finally, we show the potentialities of our methodology in order to process,
segment and classify images and arbitrary data.

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IMAGE SEGMENTATION USING FUZZY REGION
COMPETITION AND SPATIAL/FREQUENCY INFORMATION
This paper appears in: Image Processing, IEEE Transactions: June 2011

Abstract
This paper presents a multiphase fuzzy region competition model that takes into
account spatial and frequency information for image segmentation. In the
proposed energy functional, each region is represented by a fuzzy membership
function and a data fidelity term that measures the conformity of spatial and
frequency data within each region to (generalized) Gaussian densities whose
parameters are determined jointly with the segmentation process.
Compared with the classical region competition model, our approach gives soft
segmentation results via the fuzzy membership functions, and moreover, the use
of frequency data provides additional region information that can improve the
overall segmentation result.
To efficiently solve the minimization of the energy functional, we adopt an
alternate minimization procedure and make use of Chambolle's fast duality
projection algorithm.
We apply the proposed method to synthetic and natural textures as well as real-
world natural images. Experimental results show that our proposed method has
very promising segmentation performance compared with the current state-of-the-
art approaches.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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PERCEPTUAL SEGMENTATION: COMBINING IMAGE
SEGMENTATION WITH OBJECT TAGGING
Image Processing, IEEE Transactions on Issue Date: June 2011

Abstract
Human observers understand the content of an image intuitively. Based upon
image content, they perform many image-related tasks, such as creating slide
shows and photo albums, and organizing their image archives. For example, to
select photos for an album, people assess image quality based upon the main
objects in the image.
They modify colors in an image based upon the color of important objects, such
as sky, grass or skin. Serious photographers might modify each object
separately. Photo applications, in contrast, use low-level descriptors to guide
similar tasks. Typical descriptors, such as color histograms, noise level, JPEG
artifacts and overall sharpness, can guide an imaging application and safeguard
against blunders.
However, there is a gap between the outcome of such operations and the same
task performed by a person. We believe that the gap can be bridged by
automatically understanding the content of the image.
This paper presents algorithms for automatic tagging of perceptual objects in
images, including sky, skin, and foliage, which constitutes an important step
toward this goal.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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VIBE: A UNIVERSAL BACKGROUND SUBTRACTION
ALGORITHM FOR VIDEO SEQUENCES
Image Processing, IEEE Transactions on Issue Date : June 2011

ABSTRACT
This paper presents a technique for motion detection that incorporates several
innovative mechanisms. For example, our proposed technique stores, for each
pixel, a set of values taken in the past at the same location or in the
neighborhood. It then compares this set to the current pixel value in order to
determine whether that pixel belongs to the background, and adapts the model by
choosing randomly which values to substitute from the background model.
This approach differs from those based upon the classical belief that the oldest
values should be replaced first. Finally, when the pixel is found to be part of the
background, its value is propagated into the background model of a neighboring
pixel.
We describe our method in full details (including pseudo-code and the parameter
values used) and compare it to other background subtraction techniques.
Efficiency figures show that our method outperforms recent and proven state-of-
the-art methods in terms of both computation speed and detection rate.
We also analyze the performance of a downscaled version of our algorithm to the
absolute minimum of one comparison and one byte of memory per pixel. It
appears that even such a simplified version of our algorithm performs better than
mainstream techniques.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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CONTEXTUAL KERNEL AND SPECTRAL METHODS
FOR LEARNING THE SEMANTICS OF IMAGES
Image Processing, IEEE Transactions on Issue Date: June 2011

Abstract
This paper presents contextual kernel and spectral methods for learning the
semantics of images that allow us to automatically annotate an image with
keywords. First, to exploit the context of visual words within images for automatic
image annotation, we define a novel spatial string kernel to quantify the similarity
between images.
Specifically, we represent each image as a 2-D sequence of visual words and
measure the similarity between two 2-D sequences using the shared occurrences
of s -length 1-D subsequences by decomposing each 2-D sequence into two
orthogonal 1-D sequences. Based on our proposed spatial string kernel, we
further formulate automatic image annotation as a contextual keyword
propagation problem, which can be solved very efficiently by linear programming.
Unlike the traditional relevance models that treat each keyword independently,
the proposed contextual kernel method for keyword propagation takes into
account the semantic context of annotation keywords and propagates multiple
keywords simultaneously.
Significantly, this type of semantic context can also be incorporated into spectral
embedding for refining the annotations of images predicted by keyword
propagation. Experiments on three standard image datasets demonstrate that our
contextual kernel and spectral methods can achieve significantly better results
than the state of the art.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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DISTRIBUTED MULTIPLE DESCRIPTION VIDEO CODING
ON PACKET LOSS CHANNELS
Image Processing, IEEE Transactions June 2011

ABSTRACT
In this paper, we are to solve the drift problem of multiple description video
coding on packet loss channels by using state-of-the-art distributed techniques.
We first present an asymptotically optimal code design of multiple descriptions in
the Wyner-Ziv (MDWZ) setting. Then we propose a distributed multiple
description video coding (DMDVC) scheme, which performs MDWZ coding on
each nonintra coded frame.
coding, Slepian-Wolf based coding is used to exploit interframe correlations.
A bitplane extraction scheme is proposed to improve the balance between two
descriptions, so that side informations can be interchanged between the side
decoders of DMDVC with negligible quality degradation, which is crucial to robust
transmission over packet loss channels. Experiment results demonstrate the
robustness of our scheme, especially at high packet loss rates.

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SIGMATREE SOLUTIONS                        IEEE PROJECTS 2011-12
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SIZE-CONTROLLABLE REGION-OF-INTEREST IN
SCALABLE IMAGE REPRESENTATION
Image Processing, IEEE Transactions May 2011

ABSTRACT
Differentiating region-of-interest (ROI) from non-ROI in an image in terms of
relative size as well as fidelity becomes an important functionality for future visual
communication environment with a variety of display devices.
In this paper, we propose a scalable image representation with the ROI
functionality in the spatial domain, which allows us to generate a hierarchy of
images with arbitrary sizes.
The ROI functionality of our scalable representation is a result of a nonuniform
grid transformation in the spatial domain, where only the center of ROI and an
expansion parameter are to be known. Our grid transformation guarantees no
loss of information within the area of ROI.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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GRAPH REGULARIZED SPARSE CODING FOR IMAGE
REPRESENTATION
Image Processing, IEEE Transactions on May 2011

ABSTRACT
Sparse coding has received an increasing amount of interest in recent years. It is
an unsupervised learning algorithm, which finds a basis set capturing high-level
semantics in the data and learns sparse coordinates in terms of the basis set.
Originally applied to modeling the human visual cortex, sparse coding has been
shown useful for many applications. However, most of the existing approaches to
sparse coding fail to consider the geometrical structure of the data space.
In many real applications, the data is more likely to reside on a low-dimensional
submanifold embedded in the high-dimensional ambient space. It has been
shown that the geometrical information of the data is important for discrimination.
In this paper, we propose a graph based algorithm, called graph regularized
sparse coding, to learn the sparse representations that explicitly take into
account the local manifold structure of the data.
By using graph Laplacian as a smooth operator, the obtained sparse
representations vary smoothly along the geodesics of the data manifold. The
extensive experimental results on image classification and clustering have
demonstrated the effectiveness of our proposed algorithm.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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DYNAMIC CONFLICT-FREE TRANSMISSION SCHEDULING
FOR SENSOR NETWORK QUERIES
Mobile Computing, IEEE Transactions May 2011

ABSTRACT
With the emergence of high data rate sensor network applications, there is an
increasing demand for high-performance query services. To meet this challenge,
we propose Dynamic Conflict-free Query Scheduling (DCQS), a novel scheduling
technique for queries in wireless sensor networks.
In contrast to earlier TDMA protocols designed for general-purpose workloads,
DCQS is specifically designed for query services in wireless sensor networks.
DCQS has several unique features.
First, it optimizes the query performance through conflict-free transmission
scheduling based on the temporal properties of queries in wireless sensor
reconstructing the transmission schedule.
Furthermore, DCQS also provides predictable performance in terms of the
maximum achievable query rate. We provide an analytical capacity bound for
DCQS that enables DCQS to handle overload through rate control.
NS2 simulations demonstrate that DCQS significantly outperforms a
representative TDMA protocol (DRAND) and 802.11b in terms of query latency
and throughput.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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COOPERATING WITH SMARTNESS: USING
HETEROGENEOUS SMART ANTENNAS IN MULTI-HOP
WIRELESS NETWORKS
Mobile Computing, IEEE Transactions February 2011

ABSTRACT
The use of smart antennas in multi-hop wireless networks (MWNs) has garnered
significant attention over the last few years. While homogeneous MWNs with all
nodes having the same antenna capabilities will have certain applications, we
argue that MWNs with nodes having heterogeneous antenna capabilities are
more likely to be the norm due to a variety of motivating factors.
In the context of such heterogeneous smart antenna networks (HSANs), we
investigate and motivate the need for a simple form of node cooperation called
retransmit diversity. We show that while such a simple form of node cooperation
cannot bring significant benefits to homogeneous omni-directional antenna
networks, they can bring great gains to heterogeneous smart antenna networks.
We then present several key properties pertaining to node cooperation in HSANs
along with analytical reasoning. In the process, we identify a fundamental trade-
off between exploiting smart antenna gain and cooperation gain, that undermines
the ability of HSANs to leverage node cooperation to their maximum potential.
and incorporate this mechanism through the design of a simple but efficient MAC
protocol.
The performance of the MAC protocol is evaluated through ns2 simulations along
with a realistic physical layer channel model for smart antenna environments.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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CACAO: DISTRIBUTED CLIENT-ASSISTED CHANNEL
ASSIGNMENT OPTIMIZATION FOR UNCOORDINATED
WLANS
Parallel and Distributed Systems, IEEE Transactions February 2011

ABSTRACT
IEEE 802.11 WLANs are becoming more and more popular in homes and urban
areas. As compared to traditional WLAN setups (such as in campuses) where
knowledgeable network administrators can make centralized decisions on
channel selection, access points (APs) in these networks are often deployed by
network non-specialists in an uncoordinated manner, leading to unplanned
topology, interference and therefore unsatisfactory throughput performance.
We consider in this paper a distributed channel        assignment algorithm for
uncoordinated WLANs, where APs can self-configure     their operating channels to
minimize interference with adjacent APs. We first     formulate the optimization
problem on channel assignment which overcomes          some of the weaknesses
encountered by uncoordinated WLANs.
We show that the problem is NP-hard, and propose an efficient, simple and
distributed algorithm termed CACAO (Client-Assisted Channel Assignment
Optimization). In CACAO, the clients feed back their traffic information to their
channel assignment decisions at the APs.
We conduct extensive simulation study and comparisons using Network Simulator
2 (NS2). Our results show that CACAO out-performs other traditional and recent
schemes in terms of TCP and UDP throughputs with a similar level of fairness.
Furthermore, it converges quite fast and reduces co-channel interference
significantly.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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SCHEDULABILITY ANALYSIS FOR HARD NETWORK
LIFETIME WIRELESS SENSOR NETWORKS WITH HIGH
ENERGY FIRST CLUSTERING
Reliability, IEEE Transactions April 2011

ABSTRACT
Network lifetime predictability is an essential system requirement for the type of
wireless sensor network (WSN) used in safety-critical and highly-reliable
applications.
All sensor nodes in these time-critical WSNs should meet the lifetime constraint
at any time instance, else it may cause severe consequences that involve
economic losses, or even fatalities. In the literature, clustering sensors into
groups is a popular strategy to maximize the network lifetime, but none of the
clustering algorithms address the predictability issue for time-critical WSNs.
In this paper, the High Energy First (HEF) clustering algorithm is chosen as a
design reference model, which is proved in this paper to be an optimal clustering
practice, the network lifetime bounds and feasibility test for the HEF are
developed via the worst case energy consumption analysis.
The network simulator 2 (NS2) is used to verify the proposed network lifetime
predictability model, and the results show that the derived bounds of the
predictability provide accurate estimations of the system lifetime.

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SIGMATREE SOLUTIONS                         IEEE PROJECTS 2011-12
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ANOMALY DETECTION IN NETWORK TRAFFIC
BASED ON STATISTICAL INFERENCE AND
ALPHA-STABLE MODELING
Dependable and Secure Computing, IEEE Transactions July-Aug. 2011

ABSTRACT
This paper proposes a novel method to detect anomalies in network traffic, based
on a nonrestricted α-stable first-order model and statistical hypothesis testing. To
this end, we give statistical evidence that the marginal distribution of real traffic is
adequately modeled with α-stable functions and classify traffic patterns by means
of a Generalized Likelihood Ratio Test (GLRT).
The method automatically chooses traffic windows used as a reference, which the
traffic window under test is compared with, with no expert intervention needed to
that end. We focus on detecting two anomaly types, namely floods and flash-
crowds, which have been frequently studied in the literature.
Performance of our detection method has been measured through Receiver
Operating Characteristic (ROC) curves and results indicate that our method
outperforms the closely-related state-of-the-art contribution described in.
All experiments use traffic data collected from two routers at our university-a
25,000 students institution-which provide two different levels of traffic
aggregation for our tests (traffic at a particular school and the whole university).
In addition, the traffic model is tested with publicly available traffic traces. Due to
the complexity of α-stable distributions, care has been taken in designing
appropriate numerical algorithms to deal with the model.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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ELMO: ENERGY AWARE LOCAL MONITORING IN
SENSOR NETWORKS

Dependable and Secure Computing, IEEE Transactions July-Aug. 2011

ABSTRACT
Over the past decade, local monitoring has been shown to be a powerful
technique for improving security in multihop wireless sensor networks (WSNs).
Indeed, local monitoring-based security algorithms are becoming the most
popular tool for providing security in WSNs. However, local monitoring as it is
currently practiced is costly in terms of energy consumption, a major drawback
for energy-constrained systems such as WSNs. In WSN environments, the scarce
power resources are typically addressed through sleep-wake scheduling of the
nodes.
However, sleep-wake scheduling techniques in WSNs are vulnerable even to
simple attacks. In this paper, a new technique is proposed that promises to allow
operation of WSNs in a manner that is both energy-efficient and secure. The
proposed technique combines local monitoring with a novel, more secure form of
sleep-wake scheduling.
The latter is a new methodology dubbed Elmo (Energy Aware Local MOnitoring in
Sensor Networks), which enables sleep-wake management in a secure manner
even in the face of adversarial nodes that choose not to awaken nodes
responsible for monitoring their traffic.
An analytical proof is given showing that security coverage is not weakened
under Elmo. Moreover, ns-2 simulation results show that the performance of local
monitoring is practically unchanged, while energy savings of 20 to 100 times are
achieved, depending on the scenario.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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EFFICIENT FAULT DETECTION AND DIAGNOSIS IN
COMPLEX SOFTWARE SYSTEMS WITH INFORMATION-
THEORETIC MONITORING
Dependable and Secure Computing, IEEE Transactions on

ABSTRACT
Management metrics of complex software systems exhibit stable correlations
which can enable fault detection and diagnosis. Current approaches use specific
analytic forms, typically linear, for modeling correlations. In practice, more
complex nonlinear relationships exist between metrics.
Moreover, most intermetric correlations form clusters rather than simple pairwise
correlations. These clusters provide additional information and offer the
possibility for optimization. In this paper, we address these issues by using
Normalized Mutual Information (NMI) as a similarity measure to identify clusters
of correlated metrics, without assuming any specific form for the metric
relationships.
We show how to apply the Wilcoxon Rank-Sum test on the entropy measures to
detect errors in the system. We also present three diagnosis algorithms to locate
faulty components: RatioScore, based on the Jaccard coefficient, SigScore,
which incorporates knowledge of component dependencies, and BayesianScore,
which uses Bayesian inference to assign a fault probability to each component.
We evaluate our approach in the context of a complex enterprise application, and
show that 1) stable, nonlinear correlations exist and can be captured with our
approach; 2) we can detect a large fraction of faults with a low false positive rate
(we detect up to 18 of the 22 faults we injected); and 3) we improve the diagnosis
with our new diagnosis algorithms.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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CONFIDENTIAL DATABASES
Dependable and Secure Computing, IEEE Transactions on

ABSTRACT
Suppose Alice owns a k-anonymous database and needs to determine whether
her database, when inserted with a tuple owned by Bob, is still k-anonymous.
Also, suppose that access to the database is strictly controlled, because for
example data are used for certain experiments that need to be maintained
confidential. Clearly, allowing Alice to directly read the contents of the tuple
breaks the privacy of Bob (e.g., a patient's medical record); on the other hand,
the confidentiality of the database managed by Alice is violated once Bob has
Thus, the problem is to check whether the database inserted with the tuple is still
k-anonymous, without letting Alice and Bob know the contents of the tuple and
the database, respectively. In this paper, we propose two protocols solving this
problem on suppression-based and generalization-based k-anonymous and
confidential databases.
The protocols rely on well-known cryptographic assumptions, and we provide
theoretical analyses to proof their soundness and experimental results to
illustrate their efficiency.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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DYNAMICS OF MALWARE SPREAD IN DECENTRALIZED
PEER-TO-PEER NETWORKS
Dependable and Secure Computing, IEEE Transactions July-Aug. 2011

Abstract
In this paper, we formulate an analytical model to characterize the spread of
malware in decentralized, Gnutella type peer-to-peer (P2P) networks and study
the dynamics associated with the spread of malware.
Using a compartmental model, we derive the system parameters or network
conditions under which the P2P network may reach a malware free equilibrium.
The model also evaluates the effect of control strategies like node quarantine on
stifling the spread of malware. The model is then extended to consider the impact
of P2P networks on the malware spread in networks of smart cell phones.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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LOW-ENERGY SYMMETRIC KEY DISTRIBUTION IN
WIRELESS SENSOR NETWORKS
Dependable and Secure Computing, IEEE Transactions May-June 2011

ABSTRACT
In this work, a scheme for key distribution and network access in a Wireless
Sensor Network (WSN) that utilizes Identity-Based Cryptography (IBC) is
presented.
The scheme is analyzed on the ARM920T processor and measurements were
taken for the runtime and energy of its components. It was found that the Tate
pairing component of the scheme consumes significant amounts of energy, and
so should be ported to hardware.
An accelerator was implemented in 65 nm Complementary Metal Oxide Silicon
(CMOS) technology and area, timing, and energy figures have been obtained for
the design.
Results indicate that a hardware implementation of IBC would meet the strict
energy constraint required of a wireless sensor network node.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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REPLICA PLACEMENT FOR ROUTE DIVERSITY IN TREE-
BASED ROUTING DISTRIBUTED HASH TABLES
Dependable and Secure Computing, IEEE Transactions May-June 2011

ABSTRACT
Distributed hash tables (DHTs) share storage and routing responsibility among all
nodes in a peer-to-peer network. These networks have bounded path length
misroute lookups. We address both of these problems through replica placement.
We characterize tree-based routing DHTs and define MaxDisjoint, a replica
placement that creates route diversity for these DHTs. We prove that this
placement creates disjoint routes and find the replication degree necessary to
produce a desired number of disjoint routes.
Using simulations of Pastry (a tree-based routing DHT), we evaluate the impact
of MaxDisjoint on routing robustness compared to other placements when nodes
are compromised at random or in a contiguous run.
Furthermore, we consider another route diversity mechanism that we call
neighbor set routing and show that, when used with our replica placement, it can
successfully route messages to a correct replica even with a quarter of the nodes
in the system compromised at random.
Finally, we demonstrate a family of replica query strategies that can trade off
response time and system load. We present a hybrid query strategy that keeps
response time low without producing too high a load.

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SIGMATREE SOLUTIONS                               IEEE PROJECTS 2011-12
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ROBUST CORRELATION OF ENCRYPTED
ATTACK TRAFFIC THROUGH STEPPING
STONES BY FLOW WATERMARKING
Dependable and Secure Computing, IEEE Transactions May-June 2011

ABSTRACT
Network-based intruders seldom attack their victims directly from their own computer. Often,
they stage their attacks through intermediate “stepping stones” in order to conceal their identity
and origin. To identify the source of the attack behind the stepping stone(s), it is necessary to
correlate the incoming and outgoing flows or connections of a stepping stone.
To resist attempts at correlation, the attacker may encrypt or otherwise manipulate the
connection traffic. Timing-based correlation approaches have been shown to be quite effective
in correlating encrypted connections. However, timing-based correlation approaches are subject
to timing perturbations that may be deliberately introduced by the attacker at stepping stones. In
this paper, we propose a novel watermark-based-correlation scheme that is designed
specifically to be robust against timing perturbations.
Unlike most previous timing-based correlation approaches, our watermark-based approach is
“active” in that it embeds a unique watermark into the encrypted flows by slightly adjusting the
timing of selected packets. The unique watermark that is embedded in the encrypted flow gives
us a number of advantages over passive timing-based correlation in resisting timing
perturbations by the attacker.
In contrast to the existing passive correlation approaches, our active watermark-based
correlation does not make any limiting assumptions about the distribution or random process of
the original interpacket timing of the packet flow. In theory, our watermark-based correlation can
achieve arbitrarily close to 100 percent correlation true positive rate (TPR), and arbitrarily close
to 0 percent false positive rate (FPR) at the same time for sufficiently long flows, despite
arbitrarily large (but bounded) timing perturbations of any distribution by the attacker.
Our paper is the first that identifies
1) accurate quantitative tradeoffs between the achievable correlation effectiveness a- - nd
the defining characteristics of the timing perturbation; and
2) a provable upper bound on the number of packets needed to achieve a desired
correlation effectiveness, given the amount of timing perturbation.
Experimental results show that our active watermark-based correlation performs better and
requires fewer packets than existing, passive timing-based correlation methods in the presence
of random timing perturbations.

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MEASUREMENT FOR NEXT GENERATION NETWORKS
Network and Service Management, IEEE Transactions on

ABSTRACT
Internet performance measurement is commonly perceived as a high-cost
control-plane activity and until now it has tended to be implemented on top of the
network's forwarding operation.
accuracy over non-intrusiveness and cost effectiveness. In this paper, we present
the software implementation of an in-line measurement mechanism that uses
native structures of the Internet Protocol version 6 (IPv6) stack to piggyback
measurement information on data-carrying traffic as this is routed between two
points in the network.
We carefully examine the overhead associated with both the measurement
process and the measurement data, and we demonstrate that direct two-point
measurement has minimal impact on throughput and on system processing load.
The results of this paper show that adequately engineered measurement
mechanisms that exploit selective processing do not compromise the network's
forwarding efficiency, and can be deployed in an always-on manner to reveal the
true performance of network traffic over small timescales.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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ON THE IMPACT OF SECURITY PROTOCOLS ON THE
PERFORMANCE OF SNMP
Network and Service Management, IEEE Transactions March 2011

ABSTRACT
Since the early 1990s, there have been several attempts to secure the Simple
Network Management Protocol (SNMP). The third version of the protocol,
published as full standard in 2002, introduced the User-based Security Model
(USM), which comes with its own user and key-management infrastructure.
Since then, network operators have reported that deploying another user and key
management infrastructure to secure SNMP is expensive and a reason to not
deploy SNMPv3. This paper describes how existing security protocols operating
above the transport layer and below application protocols can be used to secure
SNMP.
infrastructures that are used for other network management interfaces and hence
their use can reduce the operational costs associated with securing SNMP.
Our main contribution is a detailed performance analysis of a prototype
implementation, comparing the performance of SNMPv3 over SSH, TLS, and
DTLS with other versions of SNMP.
We also discuss the differences between the various options to secure SNMP
and provide guidelines for choosing solutions to implement or deploy.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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LOCATING EQUIVALENT SERVANTS
OVER P2P NETWORKS

Network and Service Management, IEEE Transactions March 2011

ABSTRACT
While peer-to-peer networks are mainly used to locate unique resources across
the Internet, new interesting deployment scenarios are emerging. Particularly,
some applications (e.g., VoIP) are proposing the creation of overlays for the
localization of services based on equivalent servants (e.g., voice relays).
This paper explores the possible overlay architectures that can be adopted to
provide such services, showing how an unstructured solution based on a scale-
free overlay topology is an effective option to deploy in this context.
Consequently, we propose EQUATOR (EQUivalent servAnt locaTOR), an
unstructured overlay implementing the above mentioned operating principles,
based on an overlay construction algorithm that well approximates an ideal scale-
free construction model.
We present both analytical and simulation results which support our overlay
topology selection and validate the proposed architecture.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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COOPERATIVE CHANNELIZATION IN WIRELESS
NETWORKS WITH NETWORK CODING
Parallel and Distributed Systems, IEEE Transactions July 2011

ABSTRACT
In this paper, we address congestion of multicast traffic in multihop wireless
networks through a combination of network coding and resource reservation.
Network coding reduces the number of transmissions required in multicast flows,
thus allowing a network to approach its multicast capacity. In addition, it
efficiently repairs errors in multicast flows by combining packets lost at different
destinations.
However, under conditions of extremely high congestion the repair capability of
network coding is seriously degraded. In this paper, we propose cooperative
channelization, in which portions of the transmission media are allocated to links
that are congested at the point where network coding cannot efficiently repair
loss.
A health metric is proposed to allow comparison of need for channelization of
different multicast links. Cooperative channelization considers the impact of
channelization on overall network performance before resource reservation is
triggered.
Our results show that cooperative channelization improves overall network
performance while being well suited for wireless networks using network coding.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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THROUGHPUT OPTIMIZATION IN MULTIHOP WIRELESS
NETWORKS WITH MULTIPACKET RECEPTION AND
DIRECTIONAL ANTENNAS
Parallel and Distributed Systems, IEEE Transactions July 2011

ABSTRACT
Recent advances in the physical layer have enabled the simultaneous reception
of multiple packets by a node in wireless networks. We address the throughput
optimization problem in wireless networks that support multipacket reception
(MPR) capability.
The problem is modeled as a joint routing and scheduling problem, which is
known to be NP-hard. The scheduling subproblem deals with finding the optimal
schedulable sets, which are defined as subsets of links that can be scheduled or
activated simultaneously. We demonstrate that any solution of the scheduling
subproblem can be built with |E| + 1 or fewer schedulable sets, where |E| is the
number of links of the network.
This result is in contrast with previous works that stated that a solution of the
scheduling subproblem is composed of an exponential number of schedulable
sets. Due to the hardness of the problem, we propose a polynomial time scheme
based on a combination of linear programming and approximation algorithm
We illustrate the use of the scheme to study the impact of design parameters on
the performance of MPR-capable networks, including the number of transmit
interfaces, the beamwidth, and the receiver range of the antennas.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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ATTRIBUTE-BASED ACCESS CONTROL WITH EFFICIENT
REVOCATION IN DATA OUTSOURCING SYSTEMS
Parallel and Distributed Systems, IEEE Transactions on

ABSTRACT
Some of the most challenging issues in data outsourcing scenario are the
enforcement of authorization policies and the support of policy updates.
Ciphertext-policy attribute-based encryption is a promising cryptographic solution
to these issues for enforcing access control policies defined by a data owner on
outsourced data.
However, the problem of applying the attribute-based encryption in an outsourced
architecture introduces several challenges with regard to the attribute and user
revocation.
In this paper, we propose an access control mechanism using ciphertext-policy
attribute-based encryption to enforce access control policies with efficient
attribute and user revocation capability.
The fine-grained access control can be achieved by dual encryption mechanism
which takes advantage of the attribute-based encryption and selective group key
distribution in each attribute group. We demonstrate how to apply the proposed
mechanism to securely manage the outsourced data.
The analysis results indicate that the proposed scheme is efficient and secure in
the data outsourcing systems.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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NETWORK IMMUNIZATION WITH DISTRIBUTED
AUTONOMY-ORIENTED ENTITIES
Parallel and Distributed Systems, IEEE Transactions July 2011

ABSTRACT
Many communication systems,         e.g., internet, can be modeled as complex
networks. For such networks,         immunization strategies are necessary for
preventing malicious attacks or      viruses being percolated from a node to its
neighboring nodes following their   connectivities.
In recent years, various immunization strategies have been proposed and
demonstrated, most of which rest on the assumptions that the strategies can be
executed in a centralized manner and/or that the complex network at hand is
reasonably stable (its topology will not change overtime). In other words, it would
be difficult to apply them in a decentralized network environment, as often found
in the real world.
In this paper, we propose a decentralized and scalable immunization strategy
based on a self-organized computing approach called autonomy-oriented
computing (AOC) [1], [2]. In this strategy, autonomous behavior-based entities
are deployed in a decentralized network, and are capable of collectively finding
those nodes with high degrees of conductivities (i.e., those that can readily
Through experiments involving both synthetic and real-world networks, we
demonstrate that this strategy can effectively and efficiently locate highly-
connected nodes in decentralized complex network environments of various
topologies, and it is also scalable in handling large-scale decentralized networks.
We have compared our strategy with some of the well-known strategies, including
acquaintance and covering strategies on both synthetic and real-world networks.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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OPTIMIZATION OF RATE ALLOCATION WITH
DISTORTION GUARANTEE IN SENSOR NETWORKS
Parallel and Distributed Systems, IEEE Transactions on July 2011

Abstract
Lossy compression techniques are commonly used by long-term data-gathering
applications that attempt to identify trends or other interesting patterns in an
entire system since a data packet need not always be completely and
immediately transmitted to the sink. In these applications, a nonterminal sensor
node jointly encodes its own sensed data and the data received from its nearby
nodes.
The tendency for these nodes to have a high spatial correlation means that these
data packets can be efficiently compressed together using a rate-distortion
strategy.
This paper addresses the optimal rate-distortion allocation problem, which
determines an optimal bit rate of each sensor based on the target overall
distortion to minimize the network transmission cost. We propose an analytically
optimal rate-distortion allocation scheme, and we also extend it to a distributed
version.
Based on the presented allocation schemes, a greedy heuristic algorithm is
proposed to build the most efficient data transmission structure to further reduce
the transmission cost. The proposed methods were evaluated using simulations
with real-world data sets.
The simulation results indicate that the optimal allocation strategy can reduce the
transmission cost to 6~15% of that for the uniform allocation scheme.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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A DATA THROUGHPUT PREDICTION AND
OPTIMIZATION SERVICE FOR WIDELY
Parallel and Distributed Systems, IEEE Transactions June 2011

Abstract
In this paper, we present the design and implementation of an application-layer
data throughput prediction and optimization service for many-task computing in
widely distributed environments. This service uses multiple parallel TCP streams
to improve the end-to-end throughput of data transfers.
A novel mathematical model is developed to determine the number of parallel
streams, required to achieve the best network performance. This model can
predict the optimal number of parallel streams with as few as three prediction
points.
We implement this new service in the Stork Data Scheduler, where the prediction
points can be obtained using Iperf and GridFTP samplings. Our results show that
the prediction cost plus the optimized transfer time is much less than the
nonoptimized transfer time in most cases.
As a result, Stork data transfer jobs with optimization service can be completed
much earlier, compared to nonoptimized data transfer jobs.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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TOWARD EFFICIENT AND SIMPLIFIED DISTRIBUTED
DATA INTENSIVE COMPUTING
Parallel and Distributed Systems, IEEE Transactions June 2011

ABSTRACT
While the capability of computing systems has been increasing at Moore's Law,
the amount of digital data has been increasing even faster. There is a growing
need for systems that can manage and analyze very large data sets, preferably
on shared-nothing commodity systems due to their low expense.
In this paper, we describe the design and implementation of a distributed file
system called Sector and an associated programming framework called Sphere
that processes the data managed by Sector in parallel. Sphere is designed so
that the processing of data can be done in place over the data whenever
possible. Sometimes, this is called data locality.
We describe the directives Sphere supports to improve data locality. In our
experimental studies, the Sector/Sphere system has consistently performed
about 2-4 times faster than Hadoop, the most popular system for processing very
large data sets.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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NONLOCAL PDES-BASED MORPHOLOGY ON WEIGHTED
GRAPHS FOR IMAGE AND DATA PROCESSING
Image Processing, IEEE Transactions June 2011

ABSTRACT
Mathematical morphology (MM) offers a wide range of operators to address
various image processing problems. These operators can be defined in terms of
algebraic (discrete) sets or as partial differential equations (PDEs).
In this paper, we introduce a nonlocal PDEs-based morphological framework
defined on weighted graphs. We present and analyze a set of operators that
leads to a family of discretized morphological PDEs on weighted graphs.
Our formulation introduces nonlocal patch-based configurations for image
processing and extends PDEs-based approach to the processing of arbitrary data
such as nonuniform high dimensional data. Finally, we show the potentialities of
our methodology in order to process, segment and classify images and arbitrary
data.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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IMAGE SEGMENTATION USING
FUZZY REGION COMPETITION AND
SPATIAL/FREQUENCY INFORMATION

Image Processing, IEEE Transactions June 2011

ABSTRACT
This paper presents a multiphase fuzzy region competition model that takes into
account spatial and frequency information for image segmentation. In the
proposed energy functional, each region is represented by a fuzzy membership
function and a data fidelity term that measures the conformity of spatial and
frequency data within each region to (generalized) Gaussian densities whose
parameters are determined jointly with the segmentation process.
Compared with the classical region competition model, our approach gives soft
segmentation results via the fuzzy membership functions, and moreover, the use
of frequency data provides additional region information that can improve the
overall segmentation result.
To efficiently solve the minimization of the energy functional, we adopt an
alternate minimization procedure and make use of Chambolle's fast duality
projection algorithm. We apply the proposed method to synthetic and natural
textures as well as real-world natural images.
Experimental results show that our proposed method has very promising
segmentation performance compared with the current state-of-the-art
approaches.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
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PERCEPTUAL SEGMENTATION: COMBINING IMAGE
SEGMENTATION WITH OBJECT TAGGING
Image Processing, IEEE Transactions June 2011

ABSTRACT
Human observers understand the content of an image intuitively. Based upon
image content, they perform many image-related tasks, such as creating slide
shows and photo albums, and organizing their image archives. For example, to
select photos for an album, people assess image quality based upon the main
objects in the image.
They modify colors in an image based upon the color of important objects, such
as sky, grass or skin. Serious photographers might modify each object
separately. Photo applications, in contrast, use low-level descriptors to guide
Typical descriptors, such as color histograms, noise level, JPEG artifacts and
overall sharpness, can guide an imaging application and safeguard against
blunders. However, there is a gap between the outcome of such operations and
the same task performed by a person.
We believe that the gap can be bridged by automatically understanding the
content of the image. This paper presents algorithms for automatic tagging of
perceptual objects in images, including sky, skin, and foliage, which constitutes
an important step toward this goal.

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VIBE: A UNIVERSAL BACKGROUND SUBTRACTION
ALGORITHM FOR VIDEO SEQUENCES
Image Processing, IEEE Transactions June 2011

ABSTRACT
This paper presents a technique for motion detection that incorporates several
innovative mechanisms. For example, our proposed technique stores, for each
pixel, a set of values taken in the past at the same location or in the
neighborhood.
It then compares this set to the current pixel value in order to determine whether
that pixel belongs to the background, and adapts the model by choosing
randomly which values to substitute from the background model. This approach
differs from those based upon the classical belief that the oldest values should be
replaced first.
Finally, when the pixel is found to be part of the background, its value is
propagated into the background model of a neighboring pixel. We describe our
method in full details (including pseudo-code and the parameter values used) and
compare it to other background subtraction techniques.
Efficiency figures show that our method outperforms recent and proven state-of-
the-art methods in terms of both computation speed and detection rate. We also
analyze the performance of a downscaled version of our algorithm to the absolute
minimum of one comparison and one byte of memory per pixel.
It appears that even such a simplified version of our algorithm performs better
than mainstream techniques.

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
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CONTEXTUAL KERNEL AND SPECTRAL METHODS FOR
LEARNING THE SEMANTICS OF IMAGES
Image Processing, IEEE Transactions June 2011

ABSTRACT
This paper presents contextual kernel and spectral methods for learning the
semantics of images that allow us to automatically annotate an image with
keywords. First, to exploit the context of visual words within images for automatic
image annotation, we define a novel spatial string kernel to quantify the similarity
between images.
Specifically, we represent each image as a 2-D sequence of visual words and
measure the similarity between two 2-D sequences using the shared occurrences
of s -length 1-D subsequences by decomposing each 2-D sequence into two
orthogonal 1-D sequences.
Based on our proposed spatial string kernel, we further formulate automatic
image annotation as a contextual keyword propagation problem, which can be
solved very efficiently by linear programming. Unlike the traditional relevance
models that treat each keyword independently, the proposed contextual kernel
method for keyword propagation takes into account the semantic context of
annotation keywords and propagates multiple keywords simultaneously.
Significantly, this type of semantic context can also be incorporated into spectral
embedding for refining the annotations of images predicted by keyword
propagation. Experiments on three standard image datasets demonstrate that our
contextual kernel and spectral methods can achieve significantly better results
than the state of the art.

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DECISION TREES FOR UNCERTAIN DATA
ABSTRACT
Traditional decision tree classiﬁers work with data whose values are
known and precise. We extend such classiﬁers to handle data with
uncertain information, which originates from measurement/quantisation
errors, data staleness, multiple repeated measurements, etc.
The value uncertainty is represented by multiple values forming a
probability distribution function (pdf). We discover that the accuracy of
a decision tree classiﬁer can be much improved if the whole pdf, rather
than a simple statistic, is taken into account.
We extend classical decision tree building algorithms to handle data
tuples with uncertain values. Since processing pdf’s is computationally
more costly, we propose a series of pruning techniques that can greatly
improve the efficiency of the construction of decision trees.

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EXPLORING APPLICATION-LEVEL SEMANTICS
FOR DATA COMPRESSION

.QRZOHGJH DQG 'DWD (QJLQHHULQJ ,((( 7UDQVDFWLRQV RQ

ABSTRACT
Natural phenomena show that many creatures form large social groups
and move in regular patterns. However, previous works focus on finding
the movement patterns of each single object or all objects.
In this paper, we first propose an efficient distributed mining algorithm
to jointly identify a group of moving objects and discover their
movement patterns in wireless sensor networks. Afterward, we propose
a compression algorithm, called 2P2D, which exploits the obtained
group movement patterns to reduce the amount of delivered data.
The compression algorithm includes a sequence merge and an entropy
reduction phases. In the sequence merge phase, we propose a Merge
algorithm to merge and compress the location data of a group of
moving objects.
In the entropy reduction phase, we formulate a Hit Item Replacement
(HIR) problem and propose a Replace algorithm that obtains the
optimal solution. Moreover, we devise three replacement rules and
derive the maximum compression ratio.
The experimental results show that the proposed compression
algorithm leverages the group movement patterns to reduce the amount
of delivered data effectively and efficiently

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EXTENDED XML TREE PATTERN MATCHING: THEORIES AND
ALGORITHMS

.QRZOHGJH DQG 'DWD (QJLQHHULQJ ,((( 7UDQVDFWLRQV RQ

ABSTRACT
As business and enterprises generate and exchange XML data more
often, there is an increasing need for efficient processing of queries on
XML data.
Searching for the occurrences of a tree pattern query in an XML
database is a core operation in XML query processing. Prior works
demonstrate that holistic twig pattern matching algorithm is an efficient
technique to answer an XML tree pattern with parent-child (P-C) and
ancestor-descendant (A-D) relationships, as it can effectively control
the size of intermediate results during query processing.
However, XML query languages (e.g., XPath and XQuery) define more
axes and functions such as negation function, order-based axis, and
wildcards. In this paper, we research a large set of XML tree pattern,
called extended XML tree pattern, which may include P-C, A-D
relationships, negation functions, wildcards, and order restriction. We
establish a theoretical framework about “matching cross” which
demonstrates the intrinsic reason in the proof of optimality on holistic
algorithms.
Based on our theorems, we propose a set of novel algorithms to
efficiently process three categories of extended XML tree patterns. A
set of experimental results on both real-life and synthetic data sets
demonstrate the effectiveness and efficiency of our proposed theories
and algorithms.

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A PRIVACY-PRESERVING LOCATION MONITORING
SYSTEM FOR WIRELESS SENSOR NETWORKS
Monitoring personal locations with a potentially untrusted server poses
privacy threats to the monitored individuals. To this end, we propose a
privacy-preserving location monitoring system for wireless sensor
networks.
In our system, we design two in-network location anonymization
algorithms, namely, resource and quality-aware algorithms, that aim to
enable the system to provide high-quality location monitoring services
for system users, while preserving personal location privacy. Both
algorithms rely on the well-established k-anonymity privacy concept,
that is, a person is indistinguishable among k persons, to enable
trusted sensor nodes to provide the aggregate location information of
monitored persons for our system.
Each aggregate location is in a form of a monitored area A along with
the number of monitored persons residing in A, where A contains at
least k persons. The resource-aware algorithm aims to minimize
communication and computational cost, while the quality-aware
algorithm aims to maximize the accuracy of the aggregate locations by
minimizing their monitored areas.
To utilize the aggregate location information to provide location
monitoring services, we use a spatial histogram approach that
estimates the distribution of the monitored persons based on the
gathered aggregate location information. Then, the estimated
distribution is used to provide location monitoring services through
We evaluate our system through simulated experiments. The results
show that our system provides high-quality location monitoring
services for system users and guarantees the location privacy of the
monitored persons.

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ADAPTIVE CLUSTER DISTANCE BOUNDING FOR HIGH-
DIMENSIONAL INDEXING
Knowledge and Data Engineering, IEEE Transactions on

ABSTRACT
We consider approaches for similarity search in correlated, high-
dimensional data sets, which are derived within a clustering framework.
We note that indexing by “vector approximation” (VA-File), which was
proposed as a technique to combat the “Curse of Dimensionality,”
employs scalar quantization, and hence necessarily ignores
dependencies across dimensions, which represents a source of
suboptimality. Clustering, on the other hand, exploits interdimensional
correlations and is thus a more compact representation of the data set.
However, existing methods to prune irrelevant clusters are based on
bounding hyperspheres and/or bounding rectangles, whose lack of
tightness compromises their efficiency in exact nearest neighbor
search. We propose a new cluster-adaptive distance bound based on
separating hyperplane boundaries of Voronoi clusters to complement
our cluster based index.
This bound enables efficient spatial filtering, with a relatively small
preprocessing storage overhead and is applicable to euclidean and
Mahalanobis similarity measures. Experiments in exact nearest-
neighbor set retrieval, conducted on real data sets, show that our
indexing method is scalable with data set size and data dimensionality
and outperforms several recently proposed indexes.
Relative to the VA-File, over a wide range of quantization resolutions, it
is able to reduce random IO accesses, given (roughly) the same
amount of sequential IO operations, by factors reaching 100X and
more.

DATA INTEGRITY PROOFS IN CLOUD STORAGE

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ABSTRACT
Cloud computing has been envisioned as the de-facto solution to the
rising storage costs of IT Enterprises. With the high costs of data
storage devices as well as the rapid rate at which data is being
generated it proves costly for enterprises or individual users to
frequently update their hardware.
Apart from reduction in storage costs data outsourcing to the cloud also
helps in reducing the maintenance. Cloud storage moves the user’s
data to large data centers, which are remotely located, on which user
does not have any control.
However, this unique feature of the cloud poses many new security
challenges which need to be clearly understood and resolved. One of
the important concerns that need to be addressed is to assure the
customer of the integrity i.e. correctness of his data in the cloud. As the
data is physically not accessible to the user the cloud should provide a
way for the user to check if the integrity of his data is maintained or is
compromised.
In this paper we provide a scheme which gives a proof of data integrity
in the cloud which the customer can employ to check the correctness of
his data in the cloud. This proof can be agreed upon by both the cloud
and the customer and can be incorporated in the Service level
agreement (SLA). This scheme ensures that the storage at the client
side is minimal which will be beneﬁcial for thin clients.

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DATA LEAKAGE DETECTION
Knowledge and Data Engineering, IEEE Transactions on

ABSTRACT
We study the following problem: A data distributor has given sensitive
data to a set of supposedly trusted agents (third parties). Some of the
data are leaked and found in an unauthorized place (e.g., on the web or
somebody's laptop).
The distributor must assess the likelihood that the leaked data came
from one or more agents, as opposed to having been independently
gathered by other means. We propose data allocation strategies
(across the agents) that improve the probability of identifying leakages.
These methods do not rely on alterations of the released data (e.g.,
watermarks). In some cases, we can also inject “realistic but fake” data
records to further improve our chances of detecting leakage and
identifying the guilty party.

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EFFECTIVE NAVIGATION OF QUERY RESULTS BASED
ON CONCEPT HIERARCHIES
Knowledge and Data Engineering, IEEE Transactions on

ABSTRACT
Search queries on biomedical databases, such as PubMed, often return
a large number of results, only a small subset of which is relevant to the
user. Ranking and categorization, which can also be combined, have
been proposed to alleviate this information overload problem. Results
categorization for biomedical databases is the focus of this work.
A natural way to organize biomedical citations is according to their
MeSH annotations. MeSH is a comprehensive concept hierarchy used
by PubMed. In this paper, we present the BioNav system, a novel
search interface that enables the user to navigate large number of
query results by organizing them using the MeSH concept hierarchy.
First, the query results are organized into a navigation tree. At each
node expansion step, BioNav reveals only a small subset of the
concept nodes, selected such that the expected user navigation cost is
minimized.
In contrast, previous works expand the hierarchy in a predefined static
manner, without navigation cost modeling. We show that the problem of
selecting the best concepts to reveal at each node expansion is NP-
complete and propose an efficient heuristic as well as a feasible
optimal algorithm for relatively small trees.

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EFFICIENT COMPUTING OF RANGE AGGREGATES
AGAINST UNCERTAIN LOCATION BASED QUERIES
Knowledge and Data Engineering, IEEE Transactions on

ABSTRACT
In many applications, including location based services, queries are not
precise. In this paper, we study the problem of efficiently computing
range aggregates in a multi-dimensional space when the query location
is uncertain.
That is, for a set of data points P, an uncertain location based query Q
with location described by a probabilistic density function, we want to
calculate the aggregate information (e.g., count, average} and sum) of
the data points within distance gamma to Q with probability at least
theta. We propose novel, efficient techniques to solve the problem
based on a filtering-and-verification framework.
In particular, two novel filtering techniques are proposed to effectively
and efficiently remove data points from verification. Finally, we show
that our techniques can be immediately extended to solve the range
query problem. Comprehensive experiments conducted on both real
and synthetic data demonstrate the efficiency and scalability of our
techniques.

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A FUZZY SELF-CONSTRUCTING FEATURE CLUSTERING
ALGORITHM FOR TEXT CLASSIFICATION
Knowledge and Data Engineering, IEEE Transactions on

ABSTRACT
Feature clustering is a powerful method to reduce the dimensionality of
feature vectors for text classification. In this paper, we propose a fuzzy
similarity-based self-constructing algorithm for feature clustering.
The words in the feature vector of a document set are grouped into
clusters, based on similarity test. Words that are similar to each other
are grouped into the same cluster.
Each cluster is characterized by a membership function with statistical
mean and deviation. When all the words have been fed in, a desired
number of clusters are formed automatically. We then have one
extracted feature for each cluster. The extracted feature, corresponding
to a cluster, is a weighted combination of the words contained in the
cluster.
By this algorithm, the derived membership functions match closely with
and describe properly the real distribution of the training data. Besides,
the user need not specify the number of extracted features in advance,
and trial-and-error for determining the appropriate number of extracted
features can then be avoided. Experimental results show that our
method can run faster and obtain better extracted features than other
methods.

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A GENERIC MULTILEVEL ARCHITECTURE FOR TIME SERIES
PREDICTION
Knowledge and Data Engineering, IEEE Transactions on

ABSTRACT
Rapidly evolving businesses generate massive amounts of time-
stamped data sequences and cause a demand for both univariate and
multivariate time series forecasting. For such data, traditional
predictive models based on autoregression are often not sufficient to
capture complex nonlinear relationships between multidimensional
features and the time series outputs.
In order to exploit these relationships for improved time series forecasting
while also better dealing with a wider variety of prediction scenarios, a
forecasting system requires a flexible and generic architecture to
accommodate and tune various individual predictors as well as
combination methods. In reply to this challenge, an architecture for
combined, multilevel time series prediction is proposed, which is suitable
for many different universal regressors and combination methods.
The key strength of this architecture is its ability to build a diversified
ensemble of individual predictors that form an input to a multilevel
selection and fusion process before the final optimized output is
obtained. Excellent generalization ability is achieved due to the highly
boosted complementarity of individual models further enforced through
cross-validation-linked training on exclusive data subsets and
ensemble output postprocessing.
In a sample configuration with basic neural network predictors and a
mean combiner, the proposed system has been evaluated in different
scenarios and showed a clear prediction performance gain.

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ACHIEVING BOUNDED MATCHING DELAY AND
MAXIMIZED THROUGHPUT IN INFORMATION
DISSEMINATION MANAGEMENT
Network and Service Management, IEEE Transactions on

ABSTRACT
The demand for high performance information dissemination is
increasing in many applications, such as e-commerce and security
alerting systems. These applications usually require that the desired
information be matched between numerous sources and sinks based
on established subscriptions in a timely manner while a maximized
system throughput be achieved to find more matched results.
Existing work primarily focuses on only one of the two requirements,
either timeliness or throughput. This can lead to an unnecessarily
underutilized system or poor guarantees on matching delays. In this
paper, we propose an integrated solution that controls both the
matching delay and CPU utilization in information dissemination
systems to achieve bounded matching delay for high-priority
information and maximized system throughput in an example
information dissemination system.
timeliness requirements for selected low-priority information. Our
solution is based on optimal control theory for guaranteed control
accuracy and system stability.
Empirical results on a hardware testbed demonstrate that our
controllers can meet the timeliness requirements while achieving
maximized system throughput.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
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A DISTRIBUTED ALGORITHM FOR FINDING ALL BEST
SWAP EDGES OF A MINIMUM DIAMETER SPANNING TREE

ABSTRACT
Communication in networks suffers if a link fails. When the links are
edges of a tree that has been chosen from an underlying graph of all
A good policy to deal with this sort of transient link failures is swap
rerouting, where the temporarily broken link is replaced by a single
swap link from the underlying graph. A rapid replacement of a broken
precomputed.
The selection of high quality swap links is essential; it must follow the
same objective as the originally chosen communication subnetwork.
We are interested in a minimum diameter tree in a graph with edge
weights (so as to minimize the maximum travel time of messages).
Hence, each swap link must minimize (among all possible swaps) the
diameter of the tree that results from swapping. We propose a
distributed algorithm that efficiently computes all of these swap links,
and we explain how to route messages across swap edges with a
compact routing scheme.

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A DUAL FRAMEWORK AND ALGORITHMS FOR TARGETED
ONLINE DATA DELIVERY
Knowledge and Data Engineering, IEEE Transactions on

ABSTRACT
A variety of emerging online data delivery applications challenge
existing techniques for data delivery to human users, applications, or
middleware that are accessing data from multiple autonomous servers.
In this paper, we develop a framework for formalizing and comparing
pull-based solutions and present dual optimization approaches.
The first approach, most commonly used nowadays, maximizes user
utility under the strict setting of meeting a priori constraints on the
usage of system resources. We present an alternative and more
flexible approach that maximizes user utility by satisfying all users. It
does this while minimizing the usage of system resources.
We discuss the benefits of this latter approach and develop an adaptive
monitoring solution Satisfy User Profiles (SUPs). Through formal
analysis, we identify sufficient optimality conditions for SUP. Using real
(RSS feeds) and synthetic traces, we empirically analyze the behavior
of SUP under varying conditions.
Our experiments show that we can achieve a high degree of
satisfaction of user utility when the estimations of SUP closely estimate
the real event stream, and has the potential to save a significant
amount of system resources. We further show that SUP can exploit
feedback to improve user utility with only a moderate increase in
resource utilization

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A FAST MULTIPLE LONGEST COMMON SUBSEQUENCE (MLCS)
ALGORITHM
Knowledge and Data Engineering, IEEE Transactions on

ABSTRACT
Finding the longest common subsequence (LCS) of multiple strings is
an NP-hard problem, with many applications in the areas of
bioinformatics and computational genomics. Although significant efforts
have been made to address the problem and its special cases, the
increasing complexity and size of biological data require more efficient
methods applicable to an arbitrary number of strings.
In this paper, we present a new algorithm for the general case of
multiple LCS (or MLCS) problem, i.e., finding an LCS of any number of
strings, and its parallel realization. The algorithm is based on the
dominant point approach and employs a fast divide-and-conquer
technique to compute the dominant points.
When applied to a case of three strings, our algorithm demonstrates the
same performance as the fastest existing MLCS algorithm designed for
that specific case. When applied to more than three strings, our
algorithm is significantly faster than the best existing sequential
methods, reaching up to 2-3 orders of magnitude faster speed on large-
size problems.
Finally, we present an efficient parallel implementation of the algorithm.
Evaluating the parallel algorithm on a benchmark set of both random
and biological sequences reveals a near-linear speedup with respect to
the sequential algorithm.

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SAT: A SECURITY ARCHITECTURE ACHIEVING ANONYMITY AND
TRACEABILITY IN WIRELESS MESH NETWORKS
Dependable and Secure Computing, IEEE Transactions on

ABSTRACT
Anonymity has received increasing attention in the literature due to the
users' awareness of their privacy nowadays. Anonymity provides
protection for users to enjoy network services without being traced.
While anonymity-related issues have been extensively studied in
payment-based systems such as e-cash and peer-to-peer (P2P)
systems, little effort has been devoted to wireless mesh networks
(WMNs). On the other hand, the network authority requires conditional
anonymity such that misbehaving entities in the network remain
traceable.
In this paper, we propose a security architecture to ensure
unconditional anonymity for honest users and traceability of
misbehaving users for network authorities in WMNs.
The proposed architecture strives to resolve the conflicts between the
anonymity and traceability objectives, in addition to guaranteeing
fundamental       security     requirements   including    authentication,
confidentiality, data integrity, and nonrepudiation. Thorough analysis on
security and efficiency is incorporated, demonstrating the feasibility and
effectiveness of the proposed architecture.

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THE COQUOS APPROACH TO CONTINUOUS QUERIES IN
UNSTRUCTURED OVERLAYS
Knowledge and Data Engineering, IEEE Transactions on

ABSTRACT
The current peer-to-peer (P2P) content distribution systems are constricted by
their simple on-demand content discovery mechanism. The utility of these systems
can be greatly enhanced by incorporating two capabilities, namely a mechanism
through which peers can register their long term interests with the network so that
they can be continuously notified of new data items, and a means for the peers to
Although researchers have proposed a few unstructured overlay-based publish-
subscribe systems that provide the above capabilities, most of these systems
require intricate indexing and routing schemes, which not only make them highly
complex but also render the overlay network less flexible toward transient peers.
This paper argues that for many P2P applications, implementing full-fledged
publish-subscribe systems is an overkill. For these applications, we study the
alternate continuous query paradigm, which is a best-effort service providing the
above two capabilities.
We present a scalable and effective middleware, called CoQUOS, for supporting
continuous queries in unstructured overlay networks. Besides being independent
of the overlay topology, CoQUOS preserves the simplicity and flexibility of the
unstructured P2P network.
Our design of the CoQUOS system is characterized by two novel techniques,
namely cluster-resilient random walk algorithm for propagating the queries to
various regions of the network and dynamic probability-based query registration
scheme to ensure that the registrations are well distributed in the overlay.

Further, we also develop effective and efficient schemes
for providing resilience to the churn of the P2P network
among the peers. This paper studies the properties of our
algorithms through theoretical analysis. We also report

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series of experiments evaluating the effectiveness and
the costs of the proposed schemes.

LEARNING SEMI-RIEMANNIAN METRICS FOR SEMISUPERVISED
FEATURE EXTRACTION
Knowledge and Data Engineering, IEEE Transactions on

ABSTRACT
Discriminant feature extraction plays a central role in pattern
recognition and classification. Linear Discriminant Analysis (LDA) is a
traditional algorithm for supervised feature extraction. Recently,
unlabeled data have been utilized to improve LDA. However, the
intrinsic problems of LDA still exist and only the similarity among the
unlabeled data is utilized.
In this paper, we propose a novel algorithm, called Semisupervised
Semi-Riemannian Metric Map (S3RMM), following the geometric
framework of semi Riemannian manifolds. S3RMM maximizes the
discrepancy of the separability and similarity measures of scatters
formulated by using semi-Riemannian metric tensors. The metric tensor
of each sample is learned via semisupervised regression.
Our method can also be a general framework for proposing new
semisupervised algorithms, utilizing the existing discrepancy-criterion-
based algorithms. The experiments demonstrated on faces and
handwritten digits show that S3RMM is promising for semisupervised
feature extraction

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LOAD SHEDDING IN MOBILE SYSTEMS WITH
MOBIQUAL
Knowledge and Data Engineering, IEEE Transactions on

ABSTRACT
In location-based, mobile continual query (CQ) systems, two key measures of
quality-of-service (QoS) are: freshness and accuracy. To achieve freshness, the
CQ server must perform frequent query reevaluations. To attain accuracy, the CQ
server must receive and process frequent position updates from the mobile nodes.
However, it is often difficult to obtain fresh and accurate CQ results
simultaneously, due to 1) limited resources in computing and communication and
2) fast-changing load conditions caused by continuous mobile node movement.
Hence, a key challenge for a mobile CQ system is: How do we achieve the highest
possible quality of the CQ results, in both freshness and accuracy, with currently
available resources?
In this paper, we formulate this problem as a load shedding one, and develop
MobiQual-a QoS-aware approach to performing both update load shedding and
The design of MobiQual highlights three important features. 1) Differentiated load
shedding: We apply different amounts of query load shedding and update load
shedding to different groups of queries and mobile nodes, respectively. 2) Per-
query QoS specification: Individualized QoS specifications are used to maximize
the overall freshness and accuracy of the query results. 3) Low-cost adaptation:
conditions and available resources.
We conduct a set of comprehensive experiments to evaluate the effectiveness of
MobiQual. The results show that, through a careful combination of update and
query load shedding, the MobiQual approach leads to much higher freshness and
accuracy in the query results in all cases, compared to existing approaches that
lack the QoS-awareness properties of MobiQual, as well as the solutions that
perform query-only or update-only load shedding.

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MONITORING SERVICE SYSTEMS FROM A LANGUAGE-ACTION
PERSPECTIVE

Business processes are increasingly distributed and open, making them
prone to failure. Monitoring is, therefore, an important concern not only
for the processes themselves but also for the services that comprise
these processes.
We present a framework for multilevel monitoring of these service systems.
It formalizes interaction protocols, policies, and commitments that account
for standard and extended effects following the language-action
perspective, and allows specification of goals and monitors at varied
Abstraction levels.
We demonstrate how the framework can be implemented and evaluate
it with multiple scenarios that include specifying and monitoring open-
service policy commitments.

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NETWORK-CODING MULTICAST NETWORKS WITH QOS
GUARANTEES

ABSTRACT
It is well known that without admission control, network congestion is
bound to occur. However, to implement admission control is difficult in
IP-based networks, which are constructed out of the end-to-end
principle, and semantics of most major signaling protocols can only be
interpreted at the edge of the network. Even if routers can perform
admission control internally, the path computation and the state
updating activities required for setting up and tearing down each flow
will overwhelm the network.
A new QoS architecture, called a nonblocking network, has been
proposed recently, and it requires no internal admission control and can
still offer hard QoS guarantees. In this architecture, as long as each
edge node admits not more than a specified amount of traffic, the
network will never experience link congestion.
For multicast networks, the main problem with this approach is low
throughput. Conventional tree-based multicast routing algorithms lead
to a throughput so low that the nonblocking concept is rendered
impractical. In this paper, we show how network coding can solve this
problem.
We demonstrate that a nonblocking unicast network and a multicast
network share the same optimal paths, and that a nonblocking multicast
network with network coding can admit the same amount of traffic as a
nonblocking unicast network. The above conclusions apply to explicit-
routing (MPLS-like) and shortest-path routing (IP-like) networks.

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PUBLISHING SEARCH LOGS - A COMPARATIVE
STUDY OF PRIVACY GUARANTEES

Search engine companies collect the "database of intentions", the
histories of their users' search queries. These search logs are a gold
mine for researchers. Search engine companies, however, are wary of
publishing search logs in order not to disclose sensitive information.
In this paper we analyze algorithms for publishing frequent keywords,
queries and clicks of a search log. We first show how methods that
achieve variants of k-anonymity are vulnerable to active attacks. We
then demonstrate that the stronger guarantee ensured by epsilon-
differential privacy unfortunately does not provide any utility for this
problem. We then propose a novel algorithm ZEALOUS and show how
to set its parameters to achieve (epsilon, delta)-probabilistic privacy.
We also contrast our analysis of ZEALOUS with an analysis by
Korolova et al. that achieves (epsilon', delta')-indistinguishability. Our
paper concludes with a large experimental study using real applications
where we compare ZEALOUS and previous work that achieves k-
anonymity in search log publishing.
Our results show that ZEALOUS yields comparable utility to k-
anonymity while at the same time achieving much stronger privacy
guarantees.

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RANKING SPATIAL DATA BY QUALITY PREFERENCES

ABSTRACT
A spatial preference query ranks objects based on the qualities of
features in their spatial neighborhood. For example, using a real estate
agency database of flats for lease, a customer may want to rank the
flats with respect to the appropriateness of their location, defined after
aggregating the qualities of other features (e.g., restaurants, cafes,
hospital, market, etc.) within their spatial neighborhood. Such a
neighborhood concept can be specified by the user via different
functions.
It can be an explicit circular region within a given distance from the flat.
Another intuitive definition is to consider the whole spatial domain and
assign higher weights to the features based on their proximity to the
flat.
In this paper, we formally define spatial preference queries and
propose appropriate indexing techniques and search algorithms for
them. Extensively evaluation of our methods on both real and synthetic
data reveal that an optimized branch-and-bound solution is efficient and
robust with respect to different parameters.

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RITAS: SERVICES FOR RANDOMIZED INTRUSION
TOLERANCE
ABSTRACT
Randomized agreement protocols have been around for more than two
decades. Often assumed to be inefficient due to their high expected
communication and computation complexities, they have remained
overlooked by the community-at-large as a valid solution for the
deployment of fault-tolerant distributed systems.
This paper aims to demonstrate that randomization can be a very
competitive approach even in hostile environments where arbitrary
faults can occur. A stack of randomized intrusion-tolerant protocols is
described and its performance evaluated under several settings in both
local-area-network (LAN) and wide-area-network environments.
The stack provides a set of relevant services ranging from basic
communication primitives up to atomic broadcast. The experimental
evaluation shows that the protocols are efficient, especially in LAN
environments where no performance reduction is observed under
certain Byzantine faults.

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ROC: RESILIENT ONLINE COVERAGE FOR
SURVEILLANCE APPLICATIONS
ABSTRACT
We consider surveillance applications in which sensors are deployed in
large numbers to improve coverage fidelity. Previous research has
studied how to select active sensor covers (subsets of nodes that cover
the field) to efficiently exploit redundant node deployment and tolerate
unexpected node failures.
Little attention was given to studying the tradeoff between fault
tolerance and energy efficiency in sensor coverage. In this work, our
objectives are twofold. First, we aim at rapidly restoring field coverage
under unexpected sensor failures in an energy-efficient manner.
Second, we want to flexibly support different degrees of redundancy in
the field without needing centralized control.
To meet these objectives, we propose design guidelines for
applications that employ distributed cover-selection algorithms to
control the degree of redundancy at local regions in the field. In
addition, we develop a new distributed technique to facilitate switching
between active covers without the need for node synchronization.
Distributed cover selection protocols can be integrated into our referred
to as “resilient online coverage” (ROC) framework. A key novelty in
ROC is that it allows every sensor to control the degree of redundancy
and surveillance in its region according to current network conditions.
We analyze the benefits of ROC in terms of energy efficiency and fault
tolerance. Through extensive simulations, we demonstrate the
effectiveness of ROC in operational scenarios and compare its
performance with previous surveillance techniques

IMPROVING AGGREGATE RECOMMENDATION DIVERSITY USING
RANKING-BASED TECHNIQUES

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ABSTRACT
Recommender systems are becoming increasingly important to
individual users and businesses for providing personalized
recommendations. However, while the majority of algorithms proposed
in recommender systems literature have focused on improving
recommendation accuracy (as exemplified by the recent Netflix Prize
competition), other important aspects of recommendation quality, such
as the diversity of recommendations, have often been overlooked.
In this paper, we introduce and explore a number of item ranking
techniques that can generate recommendations that have substantially
higher aggregate diversity across all users while maintaining
comparable levels of recommendation accuracy.
Comprehensive empirical evaluation consistently shows the diversity
gains of the proposed techniques using several real-world rating
datasets and different rating prediction algorithms.

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IMPROVING UTILIZATION OF INFRASTRUCTURE
CLOUDS
ABSTRACT
A key advantage of Infrastructure-as-a-Service (IaaS) clouds is
on-demand access, cloud providers must either significantly
overprovision their infrastructure (and pay a high price for operating
resources with low utilization) or reject a large proportion of user
requests (in which case the access is no longer on-demand). At the
Many applications and workflows are designed for recoverable systems
where interruptions in service are expected. For instance, many
scientists utilize High Throughput Computing (HTC)-enabled resources,
such as Condor, where jobs are dispatched to available resources and
terminated when the resource is no longer available.
We propose a cloud infrastructure that combines on-demand allocation
of resources with opportunistic provisioning of cycles from idle cloud
nodes to other processes by deploying backfill Virtual Machines (VMs).
For demonstration and experimental evaluation, we extend the Nimbus
cloud computing toolkit to deploy backfill VMs on idle cloud nodes for
Initial tests show an increase in IaaS cloud utilization from 37.5% to
100% during a portion of the evaluation trace but only 6.39% overhead
cost for processing the HTC workload. We demonstrate that a shared
infrastructure between IaaS cloud providers and an HTC job
management system can be highly beneficial to both the IaaS cloud
provider and HTC users by increasing the utilization of the cloud
infrastructure (thereby decreasing the overall cost) and contributing
cycles that would otherwise be idle to processing HTC jobs.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
GOING BACK AND FORTH: EFﬁCIENT
MULTIDEPLOYMENT AND MULTISNAPSHOTTING ON
CLOUDS
ABSTRACT
Infrastructure as a Service (IaaS) cloud computing has revolutionized
the way we think of acquiring resources by introducing a simple
change: allowing users to lease computational resources from the cloud
provider’s datacenter for a short time by deploying virtual machines
(VMs) on these resources.
This new model raises new challenges in the design and development
of IaaS middleware. One of those challenges is the need to deploy a
large number (hundreds or even thousands) of VM instances
simultaneously. Once the VM instances are deployed, another
challenge is to simultaneously take a snapshot of many images and
transfer them to persistent storage to support management tasks, such
as suspend-resume and migration.
With datacenters growing rapidly and conﬁgurations becoming
heterogeneous, it is important to enable e cient concurrent deployment
and snap-shotting that are at the same time hypervisor independent
and ensure a maximum compatibility with di erent conﬁgurations.
This paper addresses these challenges by proposing a virtual ﬁle
system speciﬁcally optimized for virtual machine image storage. It is
based on a lazy transfer scheme coupled with object versioning that
handles snapshotting transparently in a hypervisor-independent
fashion, ensuring high portability for di erent conﬁgurations.
Large-scale experiments on hundreds of nodes demonstrate excellent
performance results: speedup for concurrent VM deployments ranges
from a factor of 2 up to 25, with a reduction in bandwidth utilization of
as much as 90%.

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Opp Sampige Theater, Seshadripuram, Bangalore-560020.Contact No.080-23568251/2
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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
TOWARDS ZERO RETRANSMISSION OVERHEAD: A SYMBOL
LEVEL NETWORK CODING APPROACH TO RETRANSMISSION
Mobile Computing, IEEE Transactions on August 2011

ABSTRACT
We present SYNC, a physical layer transmission scheme that
drastically reduces the cost of retransmission by introducing network
coding concepts to symbol level operation. It piggybacks a new packet
on each retransmitted packet, and exploits the previously received
packet (possibly with error) at the receiver to recover both the
retransmitted packet and the piggybacked packet.
The piggybacking is achieved through higher modulation, but it does
not decrease the decodability of the mixed packets owing to the
shown. SYNC works independently of other PHY level performance
boosting schemes such as channel coding and spatial diversity.
The proof-of-concept SYNC prototype has been implemented on a
software defined radio (SDR) platform. The measurement data shows
that under the same channel condition SYNC achieves 110 percent and
42 percent median throughput gain over traditional retransmission and
SOFT, respectively.
We also show that SYNC can be used proactively where the feedback
as to the success of the previous transmission is not available, such as

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SIGMATREE SOLUTIONS                       IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
STEALTHY ATTACKS IN WIRELESS AD HOC NETWORKS:
DETECTION AND COUNTERMEASURE
Mobile Computing, IEEE Transactions on August 2011

ABSTRACT
Stealthy packet dropping is a suite of four attacks-misrouting, power control,
identity delegation, and colluding collision-that can be easily launched against
multihop wireless ad hoc networks. Stealthy packet dropping disrupts the packet
from reaching the destination through malicious behavior at an intermediate node.
However, the malicious node gives the impression to its neighbors that it performs
the legitimate forwarding action.
Moreover, a legitimate node comes under suspicion. A popular method for
detecting attacks in wireless networks is behavior-based detection performed by
normal network nodes through overhearing the communication in their
neighborhood. This leverages the open broadcast nature of wireless
communication.
An instantiation of this technology is local monitoring. We show that local
monitoring, and the wider class of overhearing-based detection, cannot detect
stealthy packet dropping attacks. Additionally, it mistakenly detects and isolates a
legitimate node.
We present a protocol called Sadec that can detect and isolate stealthy packet
dropping attack efficiently. Sadec presents two techniques that can be overlaid on
baseline local monitoring: having the neighbors maintain additional information
about the routing path, and adding some checking responsibility to each neighbor.

better utilize local monitoring by considerably increasing
the number of nodes in a neighborhood that can do
monitoring. We show through analysis and simulation
experiments that baseline local monitoring fails to
efficiently mitigate most of the presented attacks while

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SIGMATREE SOLUTIONS                        IEEE PROJECTS 2011-12
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MAP: MULTIAUCTIONEER PROGRESSIVE AUCTION
FOR DYNAMIC SPECTRUM ACCESS
Mobile Computing, IEEE Transactions on August 2011

ABSTRACT
Cognitive radio (CR) is a promising paradigm to achieve efficient utilization of the
limited spectrum resource by allowing the unlicensed users to access the licensed
spectrum, and dynamic spectrum access (DSA) is one of the fundamental
functions of CR networks. Market-driven spectrum auction has been recognized as
an effective way to achieve DSA.
In spectrum auction, the primary spectrum owners (POs) act as auctioneers who
are willing to sell idle spectrum bands for additional revenue, and the secondary
users (SUs) act as bidders who are willing to buy spectrum bands from POs for
their services. However, conventional spectrum auction designs are restricted
within the scenario of single auctioneer.
In this paper, we study the spectrum auction with multiple auctioneers and multiple
bidders, which is more realistic for practical CR networks. We propose MAP, a
Multiauctioneer Progressive auction mechanism, in which each auctioneer
systematically raises the trading price and each bidder subsequently chooses one
auctioneer for bidding.
The equilibrium is defined as the state that no auctioneer and bidder would like to
change his decision. We show analytically that MAP converges to the equilibrium
with maximum spectrum utilization of the whole system.
We further analyze the incentive for POs and SUs joining the auction and
accepting the auction result. Simulation results show that MAP well converges to
the equilibrium, and the spectrum utilization is arbitrary closed to the global optimal
solution according to the length of step.

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SIGMATREE SOLUTIONS                      IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
ON THE EFFECTIVENESS OF MONITORING FOR
INTRUSION DETECTION IN MOBILE AD HOC
NETWORKS
Mobile Computing, IEEE Transactions on August 2011

ABSTRACT
Several intrusion detection techniques (IDTs) proposed for mobile ad
hoc networks rely on each node passively monitoring the data
forwarding by its next hop. This paper presents quantitative evaluations
of false positives and their impact on monitoring-based intrusion
Experimental results show that, even for a simple three-node
configuration, an actual ad hoc network suffers from high false
positives; these results are validated by Markov and probabilistic
models. However, this false positive problem cannot be observed by
simulating the same network using popular ad hoc network simulators,
such as ns-2, OPNET or Glomosim.
To remedy this, a probabilistic noise generator model is implemented in
the Glomosim simulator. With this revised noise model, the simulated
network exhibits the aggregate false positive behavior similar to that of
the experimental testbed. Simulations of larger (50-node) ad hoc
networks indicate that monitoring-based intrusion detection has very
high false positives.
These false positives can reduce the network performance or increase
the overhead. In a simple monitoring-based system where no
secondary and more accurate methods are used, the false positives
impact the network performance in two ways: reduced throughput in
normal networks without attackers and inability to mitigate the effect of
attacks in networks with attackers.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
OPTIMAL AND EFFICIENT GRAPH-BASED RESOURCE
ALLOCATION ALGORITHMS FOR MULTISERVICE FRAME-
BASED OFDMA NETWORKS
Mobile Computing, IEEE Transactions on August 2011

ABSTRACT
This paper addresses the resource allocation problem in Orthogonal
Frequency Division Multiple Access (OFDMA)-based wireless networks.
The resource allocation problem is posed as an optimization problem
with individual user constraints.
This formulation provides a special structure that lends to efficient
solution of the problem. We develop an optimal algorithm based on
standard graph theory and Lagrangian relaxation. Based on the special
structure of the problem, the proposed resource allocation algorithm
attains the optimal solution at a much lower complexity compared to
general-purpose optimization algorithms used by previous OFDMA
resource allocation approaches.
Moreover, the resource allocation problem solved by the proposed
algorithm supports practical features such as discrete modulation set
and multiple OFDM symbols per resource allocation decision.
Furthermore, by assuming even power allocation across the OFDM
subchannels, a suboptimal resource allocation algorithm with lower
complexity is developed.
The proposed algorithms enable the system designer to control the
tradeoffs among system performance, system complexity, and the
quality of service (QoS) experienced by the users. Extensive
simulations are conducted to evaluate the performance and complexity
of the proposed algorithms under different system operating conditions.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
IEEE Trans Image Process. 2011 Aug
HYBRID NO-REFERENCE NATURAL IMAGE QUALITY
ASSESSMENT OF NOISY, BLURRY, JPEG2000, AND JPEG
IMAGES
ABSTRACT
In this paper, we propose a new image quality assessment method
based on a hybrid of curvelet, wavelet, and cosine transforms called
hybrid no-reference (HNR) model. From the properties of natural scene
statistics, the peak coordinates of the transformed coefficient histogram
of filtered natural images occupy well-defined clusters in peak
coordinate space, which makes NR possible.
Compared to other methods, HNR has three benefits: 1) It is an NR
method applicable to arbitrary images without compromising the
prediction accuracy of full-reference methods; 2) as far as we know, it
is the only general NR method well suited for four types of filters: noise,
blur, JPEG2000, and JPEG compression; and 3) it can classify the filter
types of the image and predict filter levels even when the image is
results from the application of two different filters.
We tested HNR on very intensive video image database (our image
library) and Laboratory for Image & Video Engineering (a public library).
Results are compared to the state-of-the-art methods including peak
SNR, structural similarity, visual information fidelity, and so on.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
EFFICIENT AND ACCURATE DISCOVERY OF PATTERNS
IN SEQUENCE DATASETS
Knowledge and Data Engineering

ABSTRACT
Existing sequence mining algorithms mostly focus on mining for
subsequences. However, a large class of applications, such as
biological DNA and protein motif mining, require efficient mining of
“approximate” patterns that are contiguous.
The few existing algorithms that can be applied to find such contiguous
approximate pattern mining have drawbacks like poor scalability, lack
of guarantees in finding the pattern, and difficulty in adapting to other
applications.
In this paper, we present a new algorithm called FLAME (FLexible and
Accurate Motif DEtector). FLAME is a flexible suffix tree based
algorithm that can be used to find frequent patterns with a variety of
definitions of motif (pattern) models.
It is also accurate, as it always find the pattern if it exists. Using both
real and synthetic datasets, we demonstrate that FLAME is fast,
scalable, and outperforms existing algorithms on a variety of
performance metrics. Using FLAME, it is now possible to mine datasets
that would have been prohibitively difficult with existing tools.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
CONTINUOUS MONITORING OF DISTANCE-BASED
RANGE QUERIES
Knowledge and Data Engineering

ABSTRACT
Given a positive value r, a distance-based range query returns the
objects that lie within the distance r of the query location. In this paper,
we focus on the distance-based range queries that continuously
change their locations in a euclidean space.
We present an efficient and effective monitoring technique based on
the concept of a safe zone. The safe zone of a query is the area with a
property that while the query remains inside it, the results of the query
remain unchanged. Hence, the query does not need to be reevaluated
unless it leaves the safe zone.
Our contributions are as follows: 1) We propose a technique based on
powerful pruning rules and a unique access order which efficiently
computes the safe zone and minimizes the I/O cost. 2) We theoretically
determine and experimentally verify the expected distance a query
moves before leaving the safe zone and, for majority of queries, the
expected number of guard objects. 3) Our experiments demonstrate
that the proposed approach is close to optimal and is an order of
magnitude faster than a nai ve algorithm. 4) We also extend our
technique to monitor the queries in a road network.
Our algorithm is up to two order of magnitude faster than a nai ve
algorithm.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
ENERGY TIME SERIES FORECASTING BASED ON
PATTERN SEQUENCE SIMILARITY
Knowledge and Data Engineering

ABSTRACT
This paper presents a new approach to forecast the behavior of time
series based on similarity of pattern sequences. First, clustering
techniques are used with the aim of grouping and labeling the samples
from a data set.
Thus, the prediction of a data point is provided as follows: first, the
pattern sequence prior to the day to be predicted is extracted. Then,
this sequence is searched in the historical data and the prediction is
calculated by averaging all the samples immediately after the matched
sequence.
The main novelty is that only the labels associated with each pattern
are considered to forecast the future behavior of the time series,
avoiding the use of real values of the time series until the last step of
the prediction process.
Results from several energy time series are reported and the
performance of the proposed method is compared to that of recently
published techniques showing a remarkable improvement in the
prediction.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
JAVA Projects
NATURAL IMAGE SEGMENTATION BASED ON TREE
EQUIPARTITION, BAYESIAN FLOODING AND REGION
MERGING
Image Processing

ABSTRACT
We propose a general purpose image segmentation framework, which
involves feature extraction and classification in feature space, followed
by flooding and merging in spatial domain. Region growing is based on
the computed local measurements and distances from the distribution
of features describing the different classes. Using the properties of the
label dependent distances spatial coherence is ensured, since the
image features are described globally.
The distribution of the features for the different classes are obtained by
block-wise unsupervised clustering based on the construction of the
minimum spanning tree of the blocks' grid using the Mallows distance
and the equipartition of the resulting tree.
The final clustering is obtained by using the $k$-centroids algorithm.
With high probability and under topological constraints, connected
components of the maximum likelihood classification map are used to
compute a map of initially labelled pixels.
An efficient flooding algorithm is introduced, namely, Priority Multi-
Class Flooding Algorithm (PMCFA), that assign pixels to labels using
Bayesian dissimilarity criteria. A new region merging method, which
incorporates boundary information, is introduced for obtaining the final
segmentation map.
Therefore, the merging stage is based on region features and edge
localization. Segmentation results on the Berkeley benchmark data set
demonstrate the effectiveness of the proposed methods.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
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A FAULT-TOLERANT TOKEN BASED ATOMIC BROADCAST
ALGORITHM
Dependable and Secure Computing

ABSTRACT
Many atomic broadcast algorithms have been published in the last
twenty years. Token based algorithms represent a large class of these
algorithms. Interestingly, all the token based atomic broadcast
algorithms rely on a group membership service and none of them uses
unreliable failure detectors directly.
This paper presents the first token based atomic broadcast algorithm
that uses an unreliable failure detector instead of a group membership
service. It requires a system size that is quadratic in the number of
supported failures. The special case of a single supported failure (f = 1)
requires n = 3 processes.
We experimentally evaluate the performance of this algorithm in local
and wide area networks, in order to emphasize that atomic broadcast is
efficiently implemented by combining a failure detector and a token
based mechanism.
The evaluation shows that the new token based algorithm surpasses
the performance of the other algorithms in most small system settings.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
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AUTOMATED DERIVATION OF APPLICATION-SPECIFIC
ERROR DETECTORS USING DYNAMIC ANALYSIS
IEEE Transactions on Dependable and Secure Computing

ABSTRACT
This paper proposes a novel technique for preventing a wide range of
data errors from corrupting the execution of applications. The proposed
technique enables automated derivation of fine-grained, application-
specific error detectors based on dynamic traces of application
execution.
The technique derives a set of error detectors using rule-based
templates to maximize the error detection coverage for the application.
A probability model is developed to guide the choice of the templates
and their parameters for error-detection.
The paper also presents an automatic framework for synthesizing the
set of detectors in hardware to enable low-overhead, run-time checking
of the application. The coverage of the derived detectors is evaluated
using fault injection experiments, while the performance and area
overhead of the detectors is evaluated by synthesizing them on
reconfigurable hardware.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
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REAL-TIME DETECTION OF CLONE ATTACKS IN
WIRELESS SENSOR NETWORKS
IEEE Transactions on Dependable and Secure Computing

ABSTRACT
A central problem in sensor network security is that sensors are
susceptible to physical capture attacks. Once a sensor is compromised,
the adversary can easily launch {\it clone attacks} by replicating the
compromised node, distributing the clones throughout the network, and
starting a variety of insider attacks.
Previous works against clone attacks suffer from either a high
communication/storage overhead or a poor detection accuracy. In this
paper, we propose a novel scheme for detecting clone attacks in
sensor networks, which computes for each sensor a social fingerprint
by extracting the neighborhood characteristics, and verifies the
legitimacy of the originator for each message by checking the enclosed
fingerprint.
The fingerprint generation is based on the super imposed $s$-disjunct
code, which incurs a very light communication and computation
overhead. The fingerprint verification is conducted at both the base
station and the neighboring sensors, which ensures a high detection
probability.
The security and performance analysis indicate that our algorithm can
identify clone attacks with a high detection probability at the cost of a
low computation/communication/storage overhead. To our best
knowledge, our scheme is the first to provide realtime detection of
clone attacks in an effective and efficient way.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
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EFFICIENT TOP-K APPROXIMATE SUBTREE MATCHING IN
SMALL MEMORY
Knowledge and Data Engineering, IEEE Transactions on Aug. 2011

ABSTRACT
We consider the Top-k Approximate Subtree Matching (TASM)
problem: finding the k best matches of a small query tree within a large
document tree using the canonical tree edit distance as a similarity
measure between subtrees.
Evaluating the tree edit distance for large XML trees is difficult: the best
known algorithms have cubic runtime and quadratic space complexity,
and, thus, do not scale. Our solution is TASM-postorder, a memory-
efficient and scalable TASM algorithm. We prove an upper bound for
the maximum subtree size for which the tree edit distance needs to be
evaluated.
The upper bound depends on the query and is independent of the
document size and structure. A core problem is to efficiently prune
subtrees that are above this size threshold. We develop an algorithm
based on the prefix ring buffer that allows us to prune all subtrees
above the threshold in a single postorder scan of the document.
The size of the prefix ring buffer is linear in the threshold. As a result,
the space complexity of TASM-postorder depends only on k and the
query size, and the runtime of TASM-postorder is linear in the size of
the document. Our experimental evaluation on large synthetic and real
XML documents confirms our analytic results.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
Promise for the Best Projects
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TWO EFFICIENT LABEL-EQUIVALENCE-BASED
CONNECTED-COMPONENT LABELING ALGORITHMS FOR
3-D BINARY IMAGES
Image Processing, IEEE Transactions on Aug. 2011

ABSTRACT
Whenever one wants to distinguish, recognize, and/or measure objects
(connected components) in binary images, labeling is required. This
paper presents two efficient label-equivalence-based connected-
component labeling algorithms for 3-D binary images.
One is voxel based and the other is run based. For the voxel-based
one, we present an efficient method of deciding the order for checking
voxels in the mask. For the run-based one, instead of assigning each
foreground voxel, we assign each run a provisional label. Moreover, we
use run data to label foreground voxels without scanning any
background voxel in the second scan.
Experimental results have demonstrated that our voxel-based algorithm
is efficient for 3-D binary images with complicated connected
components, that our run-based one is efficient for those with simple
connected components, and that both are much more efficient than
conventional 3-D labeling algorithms.

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SIGMATREE SOLUTIONS                     IEEE PROJECTS 2011-12
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IEEE Trans Image Processing. 2011 Aug
RATE CONTROL SCHEME FOR CONSISTENT VIDEO
QUALITY IN SCALABLE VIDEO CODEC

ABSTRACT
Multimedia data delivered to mobile devices over wireless channels or
the Internet are complicated by bandwidth fluctuation and the variety of
mobile devices. Scalable video coding has been developed as an
extension of H.264/AVC to solve this problem.
Since scalable video codec provides various scalabilities to adapt the
bitstream for the channel conditions and terminal types, scalable codec
is one of the useful codecs for wired or wireless multimedia
communication systems, such as IPTV and streaming services. In such
scalable multimedia communication systems, video quality fluctuation
It is important to efficiently use the target bits in order to maintain a
consistent video quality or achieve a small distortion variation
throughout the whole video sequence. The scheme proposed in this
paper provides a useful function to control video quality in applications
supporting scalability, whereas conventional schemes have been
proposed to control video quality in the H.264 and MPEG-4 systems.
The proposed algorithm decides the quantization parameter of the
enhancement layer to maintain a consistent video quality throughout
the entire sequence. The video quality of the enhancement layer is
controlled based on a closed-form formula which utilizes the residual
data and quantization error of the base layer.
The simulation results show that the proposed algorithm controls the
frame quality of the enhancement layer in a simple operation, where the
parameter decision algorithm is applied to each frame.

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