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IEEE Projects 2012-2013 Cloud Computing

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IEEE Projects 2012-2013 Cloud Computing Powered By Docstoc
					            Elysium Technologies Private Limited
            Approved by ISO 9001:2008 and AICTE for SKP Training
            Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
            http://www.elysiumtechnologies.com, info@elysiumtechnologies.com


     IEEE FINAL YEAR PROJECTS 2012 – 2013
                           Cloud Computing
Corporate Office: Madurai
    227-230, Church road, Anna nagar, Madurai – 625 020.
    0452 – 4390702, 4392702, +9199447933980
    Email: info@elysiumtechnologies.com, elysiumtechnologies@gmail.com
    Website: www.elysiumtechnologies.com

Branch Office: Trichy
    15, III Floor, SI Towers, Melapudur main road, Trichy – 620 001.
    0431 – 4002234, +919790464324.
    Email: trichy@elysiumtechnologies.com, elysium.trichy@gmail.com.
    Website: www.elysiumtechnologies.com

Branch Office: Coimbatore
    577/4, DB Road, RS Puram, Opp to KFC, Coimbatore – 641 002.
    +919677751577
    Website: Elysiumtechnologies.com, Email: info@elysiumtechnologies.com

Branch Office: Kollam
    Surya Complex, Vendor junction, Kollam – 691 010, Kerala.
    0474 – 2723622, +919446505482.
    Email: kerala@elysiumtechnologies.com.
    Website: www.elysiumtechnologies.com

Branch Office: Cochin
    4th Floor, Anjali Complex, near south over bridge, Valanjambalam,
    Cochin – 682 016, Kerala.
    0484 – 6006002, +917736004002.
    Email: kerala@elysiumtechnologies.com, Website: www.elysiumtechnologies.com


     IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
                           Elysium Technologies Private Limited
                           Approved by ISO 9001:2008 and AICTE for SKP Training
                           Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
                           http://www.elysiumtechnologies.com, info@elysiumtechnologies.com


                             CLOUD COMPUTING                                                             2012 – 2013

EGC     A Cloud-Based Scheme for Protecting Source-Location Privacy against Hotspot-
3201    Locating Attack in Wireless Sensor Networks

        A In wireless sensor networks, adversaries can make use of traffic information to locate the monitored objects, e.g., to
        hunt endangered animals or kill soldiers. In this paper, we first define a hotspot phenomenon that causes an obvious
        inconsistency in the network traffic pattern due to a large volume of packets originating from a small area. Second, we
        develop a realistic adversary model, assuming that the adver-sary can monitor the network traffic in multiple areas,
        rather than the entire network or only one area. Using this model, we introduce a novel attack called Hotspot-Locating
        where the adversary uses traffic analysis techniques to locate hotspots. Finally, we propose a cloud-based scheme for
        efficiently pro-tecting source nodes' location privacy against Hotspot-Locating attack by creating a cloud with an
        irregular shape of fake traffic, to counteract the inconsistency in the traffic pat-tern and camouflage the source node in
        the nodes forming the cloud. To reduce the energy cost, clouds are active only during data transmission and the
        intersection of clouds creates a larger merged cloud, to reduce the number of fake packets and also boost privacy
        preservation. Simulation and analyti-cal results demonstrate that our scheme can provide stronger privacy protection
        than routing-based schemes and requires much less energy than global-adversary-based schemes.




EGC
3202
        A Dataflow-Based Scientific Workflow Composition Framework


       Scientific workflow has recently become an enabling technology to automate and speed up the scientific discovery
       process. Although several scientific workflow management systems (SWFMSs) have been developed, a formal scientific
       workflow composition model in which workflow constructs are fully compositional one with another is still missing. In
       this paper, we propose a dataflow-based scientific workflow composition framework consisting of (1) a dataflow-based
       scientific workflow model that separates the declaration of the workflow interface from the definition of its functional
       body; (2) a set of workflow constructs, including Map, Reduce, Tree, Loop, Conditional, and Curry, which are fully
       compositional one with another; (3) a dataflow-based exception handling approach to support hierarchical exception
       propagation and user-defined exception handling. Our workflow composition framework is unique in that workflows are
       the only operands for composition; in this way, our approach elegantly solves the two-world problem in existing
       composition frameworks, in which composition needs to deal with both the world of tasks and the world of workflows.
       The proposed framework is implemented and several case studies are conducted to validate our techniques.




                IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
                          Elysium Technologies Private Limited
                           Approved by ISO 9001:2008 and AICTE for SKP Training
                          Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
                          http://www.elysiumtechnologies.com, info@elysiumtechnologies.com




 EGC    A Secure Erasure Code-Based Cloud Storage System with Secure Data Forwarding
 3203


        A cloud storage system, consisting of a collection of storage servers, provides long-term storage services over the
        Internet. Storing data in a third party's cloud system causes serious concern over data confidentiality. General
        encryption schemes protect data confidentiality, but also limit the functionality of the storage system because a few
        operations are supported over encrypted data. Constructing a secure storage system that supports multiple functions
        is challenging when the storage system is distributed and has no central authority. We propose a threshold proxy re-
        encryption scheme and integrate it with a decentralized erasure code such that a secure distributed storage system is
        formulated. The distributed storage system not only supports secure and robust data storage and retrieval, but also
        lets a user forward his data in the storage servers to another user without retrieving the data back. The main technical
        contribution is that the proxy re-encryption scheme supports encoding operations over encrypted messages as well as
        forwarding operations over encoded and encrypted messages. Our method fully integrates encrypting, encoding, and
        forwarding. We analyze and suggest suitable parameters for the number of copies of a message dispatched to storage
        servers and the number of storage servers queried by a key server. These parameters allow more flexible adjustment
        between the number of storage servers and robustness.



EGC     A Stable Network-Aware VM Placement for Cloud Systems
3204


        Virtual Machine (VM) placement has to carefully consider the aggregated resource consumption of co-located VMs in
        order to obey service level agreements at lower possible cost. In this paper, we focus on satisfying the traffic demands
        of the VMs in addition to CPU and memory requirements. This is a much more complex problem both due to its
        quadratic nature (being the communication between a pair of VMs) and since it involves many factors beyond the
        physical host, like the network topologies and the routing scheme. Moreover, traffic patterns may vary over time and
        predicting the resulting effect on the actual available bandwidth between hosts within the data center is extremely
        difficult. We address this problem by trying to allocate a placement that not only satisfies the predicted communication
        demand but is also resilient to demand time-variations. This gives rise to a new optimization problem that we call the
        Min Cut Ratio-aware VM Placement (MCRVMP). The general MCRVMP problem is NP-Hard, hence, we introduce several
        heuristics to solve it in reasonable time. We present extensive experimental results, associated with both placement
        computation and run-time performance under time-varying traffic demands, to show that our heuristics provide good
        results (compared to the optimal solution) for medium size data centers.

EGC     A Time-Series Pattern Based Noise Generation Strategy for Privacy Protection in Cloud
3205
        Computing


                IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
                          Elysium Technologies Private Limited
                          Approved by ISO 9001:2008 and AICTE for SKP Training
                          Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
                          http://www.elysiumtechnologies.com, info@elysiumtechnologies.com

       Cloud computing promises an open environment where customers can deploy IT services in a pay-as-you-go fashion
       while saving huge capital investment in their own IT infrastructure. Due to the openness, various malicious service
       providers may exist. Such service providers may record service information in a service process from a customer and
       then collectively deduce the customer's private information. Therefore, from the perspective of cloud computing
       security, there is a need to take special actions to protect privacy at client sides. Noise obfuscation is an effective
       approach in this regard by utilising noise data. For instance, it generates and injects noise service requests into real
       customer service requests so that service providers would not be able to distinguish which requests are real ones if
       their occurrence probabilities are about the same. However, existing typical noise generation strategies mainly focus
       on the entire service usage period to achieve about the same final occurrence probabilities of service requests. In fact,
       such probabilities can fluctuate in a time interval such as three months and may significantly differ than other time
       intervals. In this case, service providers may still be able to deduce the customers' privacy from a specific time interval
       although unlikely from the overall period. That is to say, the existing typical noise generation strategies could fail to
       protect customers' privacy for local time intervals. To address this problem, we develop a novel time-series pattern
       based noise generation strategy. Firstly, we analyse previous probability fluctuations and propose a group of time-
       series patterns for predicting future fluctuated probabilities. Then, based on these patterns, we present our strategy by
       forecasting future occurrence probabilities of real service requests and generating noise requests to reach about the
       same final probabilities in the next time interval. The simulation evaluation demonstrates that our strateg- can cope
       with these fluctuations to significantly improve the effectiveness of customers' privacy protection.



EGC    An Autonomous Reliability-Aware Negotiation Strategy for Cloud Computing
3206   Environments


       Cloud computing paradigm allows subscription-based access to computing and storages services over the Internet.
       Since with advances of Cloud technology, operations such as discovery, scaling, and monitoring are accomplished
       automatically, negotiation between Cloud service requesters and providers can be a bottleneck if it is carried out by
       humans. Therefore, our objective is to offer a state-of-the-art solution to automate the negotiation process in Cloud
       environments. In previous works in the SLA negotiation area, requesters trust whatever QoS criteria values providers
       offer in the process of negotiation. However, the proposed negotiation strategy for requesters in this work is capable of
       assessing reliability of offers received from Cloud providers. In addition, our proposed negotiation strategy for Cloud
       providers considers utilization of resources when it generates new offers during negotiation and concedes more on the
       price of less utilized resources. The experimental results show that our strategy helps Cloud providers to increase their
       profits when they are participating in parallel negotiation with multiple requesters.


EGC    Building crawler engine on cloud computing infrastructure
3207


       This paper is aimed to create implementation crawler engine or search engine using cloud computing infrastructure.
       This approach use virtual machines on a cloud computing infrastructure to run service engine crawlers and also for


               IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
                           Elysium Technologies Private Limited
                           Approved by ISO 9001:2008 and AICTE for SKP Training
                           Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
                           http://www.elysiumtechnologies.com, info@elysiumtechnologies.com

        application servers. Based on our initial experiments, this research has successfully built crawler engine that runs on
        Virtual Machine (VM) of cloud computing infrastructure. The use of Virtual Machine (VM) on this architecture will help to
        ease setup or installation, maintenance or VM terminating that has been running with some particular service crawler
        engine as needed. With this infrastructure, the increasing or decreasing in capacity and capability of multiple engine
        crawlers could set easily and more efficiently.


EGC     Client Classification Policies for SLA Enforcement in Shared Cloud Datacenters
3208


        In Utility computing business model, the owners of the computing resources negotiate with their potential clients to sell
        computing power. The terms of the Quality of Service (QoS) and the economic conditions are established in a Service-
        Level Agreement (SLA). There are many scenarios in which the agreed QoS cannot be provided because of errors in the
        service provisioning or failures in the system. Since providers have usually different types of clients, according to their
        relationship with the provider or by the fee that they pay, it is important to minimize the impact of the SLA violations in
        preferential clients. This paper proposes a set of policies to provide better QoS to preferential clients in such
        situations. The criterion to classify clients is established according to the relationship between client and provider
        (external user, internal or another privileged relationship) and the QoS that the client purchases (cheap contracts or
        extra QoS by paying an extra fee). Most of the policies use key features of virtualization: Selective Violation of the
        SLAs, Dynamic Scaling of the Allocated Resources, and Runtime Migration of Tasks. The validity of the policies is
        demonstrated through exhaustive experiments.


 EGC     COCA: Computation Offload to Clouds Using AOP
 3209


        In this paper, we describe COCA -- Computation Offload to Clouds using AOP (aspect-oriented programming). COCA is
        a programming framework that allows smart phones application developers to offload part of the computation to
        servers in the cloud easily. COCA works at the source level. By harnessing the power of AOP, COCA inserts
        appropriate offloading code into the source code of the target application based on the result of static and dynamic
        profiling. As a proof of concept, we integrate COCA into the Android development environment and fully automate the
        new build process, making application programming and software maintenance easier. With COCA, mobile applications
        can now automatically offload part of the computation to the cloud, achieving better performance and longer battery
        life. Smart phones such as iPhone and Android phones can now easily leverage the immense computing power of the
        cloud to achieve tasks that were considered difficult before, such as having a more complicated artificial-intelligence
        engine.


 EGC     Efficient Resource Mapping Framework over Networked Clouds via Iterated Local Search
 3210
         based Request Partitioning

        The Cloud represents a computing paradigm where shared configurable resources are provided as a service over the


                  IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
                           Elysium Technologies Private Limited
                           Approved by ISO 9001:2008 and AICTE for SKP Training
                           Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
                           http://www.elysiumtechnologies.com, info@elysiumtechnologies.com

        Internet. Adding intra or inter cloud communication resources to the resource mix leads to a networked cloud
        computing environment. Following the Cloud Infrastructure as a Service paradigm and in order to create a flexible
        management framework, it is of paramount importance to address efficiently the resource mapping problem within this
        context. To deal with the inherent complexity and scalability issue of the resource mapping problem across different
        administrative domains, in this article a hierarchical framework is described. First, a novel request partitioning
        approach based on Iterated Local Search is introduced that facilitates the cost-efficient and on-line splitting of user
        requests among eligible Cloud service Providers (CPs) within a networked cloud environment. Following and
        capitalizing on the outcome of the request partitioning phase, the embedding phase - where the actual mapping of
        requested virtual to physical resources is performed – can be realized through the use of a distributed intra-
        cloud resource mapping approach that allows for efficient and balanced allocation of cloud resources. Finally, a
        thorough evaluation of the proposed overall framework on a simulated networked cloud environment is provided and
        critically compared against an exact request partitioning solution as well as another common intra-domain virtual
        resource embedding solution.


EGC    Energy-Aware Autonomic Resource Allocation in Multitier Virtualized Environments
3211


        In wireless sensor networks, adversaries can make use of traffic information to locate the monitored objects, e.g., to
        hunt endangered animals or kill soldiers. In this paper, we first define a hotspot phenomenon that causes an obvious
        inconsistency in the network traffic pattern due to a large volume of packets originating from a small area. Second, we
        develop a realistic adversary model, assuming that the adver-sary can monitor the network traffic in multiple areas,
        rather than the entire network or only one area. Using this model, we introduce a novel attack called Hotspot-Locating
        where the adversary uses traffic analysis techniques to locate hotspots. Finally, we propose a cloud-based scheme for
        efficiently pro-tecting source nodes' location privacy against Hotspot-Locating attack by creating a cloud with an
        irregular shape of fake traffic, to counteract the inconsistency in the traffic pat-tern and camouflage the source node in
        the nodes forming the cloud. To reduce the energy cost, clouds are active only during data transmission and the
        intersection of clouds creates a larger merged cloud, to reduce the number of fake packets and also boost privacy
        preservation. Simulation and analyti-cal results demonstrate that our scheme can provide stronger privacy protection
        than routing-based schemes and requires much less energy than global-adversary-based schemes.


EGC     Environmental and disaster sensing using cloud computing infrastructure
3212


       The remote monitoring system is growing very rapidly due to the growth of supporting technologies as well. Problem
       that may occur in remote monitoring such as the number of objects to be monitored and how fast, how much data to be
       transmitted to the data center to be processed properly. This study proposes using a cloud computing infrastructure as
       processing center in the remote sensing data. This study focuses on the situation for sensing on the environment
       condition and disaster early detection. Where those two things, it has become an important issue, especially in big cities
       big cities that have many residents. This study proposes to build the conceptual and also prototype model in a

                IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
                            Elysium Technologies Private Limited
                             Approved by ISO 9001:2008 and AICTE for SKP Training
                            Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
                            http://www.elysiumtechnologies.com, info@elysiumtechnologies.com

       comprehensive manner from the remote terminal unit until development method for data retrieval. We also propose
       using FTR-HTTP method to guarantee the delivery from remote client to server.




EGC     Framework on large public sector implementation of cloud computing
3213


       Cloud computing enables IT systems to be scalable and elastic. One significant advantage of it is users no longer need
       to determine their exact computing resource requirements upfront. Instead, they request computing resources as
       required, on-demand. This paper is written to introduce a framework specific for large public sector entities on how to
       migrate to cloud computing. This paper can then be also be a reference for the Organizations to overcome its limitations
       and to convince their stakeholders to further implement various types of Cloud Computing service models.




EGC     Identification of SME readiness to implement cloud computing
3214


       Cloud Computing allows the use of information technology based on the on-demand utility. This technology can provide
       benefits to small and medium enterprises with limited capital, human resources, and access to marketing network. A
       survey conducted on SMEs in the district of Coblong Bandung to dig up the IT needs and analyze their readiness to
       adopt cloud computing technologies. The survey results stated that SMEs' respondents are more suitable to implement
       Software as a Service with public cloud deployment method. SMEs are ready to implement this technology, but require
       appropriate training and role models that can be used as an example because their technology adoption characteristics
       that are late majority.




EGC     Interactive 3D visualization of soical network data using cloud computing
3215


       The social networks have revolutionized the online communication and data sharing. The researchers are now focusing
       on mining and analysis of large amount of social network data for a variety of purposes. However, because of the huge
       amount of continuously changing data, the data analysis in a daunting task. OLAP analysis is a famous data analysis
       method which can be used to analyze social data. This work extends our previous work in which we developed
       interactive 3D visual data cubes for high volume/dimension OLAP data analysis. The implementation of this scheme on
       traditional computing resources is much time consuming and resource intensive. The advances in cloud computing
       motivated us to use the cost effective cloud computing for the task of 3D visualization of social networks data.
       Therefore, in this paper, we propose the usage of cloud computing platforms as a possible solution for analyzing large
       amount of social network data. .




                 IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
                           Elysium Technologies Private Limited
                           Approved by ISO 9001:2008 and AICTE for SKP Training
                           Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
                           http://www.elysiumtechnologies.com, info@elysiumtechnologies.com



EGC     MORPHOSYS: Efficient Colocation of QoS-Constrained Workloads in the Cloud
3216


       In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use
       of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for
       unencumbered use for proper operation. Arbitrary colocation of applications with different SLAs on a single host may
       result in inefficient utilization of the host's resources. In this paper, we propose that periodic resource allocation and
       consumption models -- often used to characterize real-time workloads -- be used for a more granular expression of
       SLAs. Our proposed SLA model has the salient feature that it exposes flexibilities that enable the infrastructure provider
       to safely transform SLAs from one form to another for the purpose of achieving more efficient colocation. Towards that
       goal, we present MORPHOSYS: a framework for a service that allows the manipulation of SLAs to enable efficient
       colocation of arbitrary workloads in a dynamic setting. We present results from extensive trace-driven simulations of
       colocated Video-on-Demand servers in a cloud setting. These results show that potentially-significant reduction in
       wasted resources (by as much as 60%) are possible using MORPHOSYS.




EGC     On Handling Large-Scale Polynomial Multiplications in Compute Cloud Environments
3217
        using Divisible Load Paradigm

       Large-scale polynomial product computations often used in aerospace applications such as satellite image processing
       and sensor networks data processing always pose considerable challenge when processed on networked computing
       systems. With non-zero communication and computation time delays of the links and processors on a networked
       infrastructure, the computation becomes all the more challenging. In this research, we attempt to investigate the use of a
       divisible load paradigm to design efficient strategies to minimize the overall processing time for performing large-scale
       polynomial product computations in compute cloud environments. We consider a compute cloud system with the
       resource allocator distributing the entire load to a set of virtual CPU instances (VCI) and the VCIs propagating back the
       processed results to resource allocator for postprocessing. We consider heterogeneous networks in our analysis and
       we derive fundamental recursive equations and a closed-form solution for the load fractions to be assigned to each VCI.
       Our analysis also attempts to eliminate any redundant VCI-link pairs by carefully considering the overheads associated
       with load distribution and processing. Finally, we quantify the performance of the strategies via rigorous simulation
       studies.




EGC     Optimal Multiserver Configuration for Profit Maximization in Cloud Computing
3218

       As cloud computing becomes more and more popular, understanding the economics of cloud computing becomes
       critically important. To maximize the profit, a service provider should understand both service charges and business

                  IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
                           Elysium Technologies Private Limited
                           Approved by ISO 9001:2008 and AICTE for SKP Training
                           Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
                           http://www.elysiumtechnologies.com, info@elysiumtechnologies.com

       costs, and how they are determined by the characteristics of the applications and the configuration of a multiserver
       system. The problem of optimal multiserver configuration for profit maximization in a cloud computing environment is
       studied. Our pricing model takes such factors into considerations as the amount of a service, the workload of an
       application environment, the configuration of a multiserver system, the service level agreement, the satisfaction of a
       consumer, the quality of a service, the penalty of a low quality service, the cost of renting, the cost of energy
       consumption, and a service provider's margin and profit. Our approach is to treat a multiserver system as an M/M/m
       queueing model, such that our optimization problem can be formulated and solved analytically. Two server speed and
       power consumption models are considered, namely, the idle-speed model and the constant-speed model. The
       probability density function of the waiting time of a newly arrived service request is derived. The expected service
       charge to a service request is calculated. The expected net business gain in one unit of time is obtained. Numerical
       calculations of the optimal server size and the optimal server speed are demonstrated.


EGC      Optimization of Resource Provisioning Cost in Cloud Computing
3219



       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 pay to provider in advance. 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 the 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.



EGC      Policy-Based Automation of SLA Establishment for Cloud Computing Services
3220



       We propose a policy-based framework for the automated establishment of SLAs for cloud computing services. The
       proposed framework supports multiple interaction models for SLA establishment giving consumers and providers the
       flexibility to choose one that is most appropriate in a given context, while simultaneously supporting multiple
       concurrent SLA interactions using different interaction models. We describe the underlying policies, focussing on the
       key features and contributions of the framework. We also validate our framework through a real-world use-case scenario
       using the Amazon EC2 service.


                IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
                           Elysium Technologies Private Limited
                           Approved by ISO 9001:2008 and AICTE for SKP Training
                           Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
                           http://www.elysiumtechnologies.com, info@elysiumtechnologies.com

EGC
        Privacy Mechanism for Applications in Cloud Computing
3221


       Applications stored in the cloud enable users to access and perform tasks in real time, reducing costs in the acquisition
       of computer resources. Although there are benefits, this paradigm also brings security and privacy risks to users, such
       as theft of information or identity. This paper proposes a mechanism able to provide privacy protection for users to use
       applications that address issues of identity, confidentiality and user preferences.


EGC
       Real-time rendering for massive terrain data using GPUs
3222


       Real-time rendering for massive terrain data is a challenging work. Previous GPUs are not suitable for rendering
       massive mesh data. Recently, with tessellation shaders and geometry shader added on a GPU, it is possible to tessellate
       triangles or quad patches to improve geometrical features of mesh objects. In this paper, we propose a massive terrain
       rendering technique in real-time using GPUs. We made displacement and normal map from massive terrain data on the
       GPU. As a result, we could tessellate a coarse base mesh with a high resolution texture as displacement map and
       normal map for shading from massive terrain data.


EGC
3223
        RO-BURST: A Robust Virtualization Cost Model for Workload Consolidation over Clouds


       As more public cloud computing platforms are emerging in the market, a great challenge for these Infrastructure as a
       Server (IaaS) providers is how to measure the cost and charge the Software as a Service (SaaS) clients for the cloud
       computing services. This problem is compounded as virtualization technology is deployed in many cloud platforms to
       consolidate servers and improve their utilization. This paper studies three different but related models for apportioning
       costs in a private or public cloud environment supported by virtualized data centers. With given workload placement
       scenarios and randomly selected workloads, these models estimate the cost for each workload. Through simulations
       and thorough comparisons of the results, we finally champion the RO-BURST model tailored for the service providers'
       need, that is characterized by robustness and burstiness. What is more, we import Cost Volatility Factors to ensure that
       our model is able to adjust itself to the market and multiform demands in power and hardware components, such as
       disks and CPU, showing its compatibility and extensibility. We also come up with a pricing strategy with respect to
       servers the workload employs, which generates an applicable and less placement-sensitive fee for the clients


EGC
        Service Level Agreement for Distributed Mutual Exclusion in Cloud Computing
3224


       In Cloud Computing, Service Level Agreement (SLA) is a contract that defines a level and a type of QoS between a cloud
       provider and a client. Since applications in a Cloud share resources, we propose two tree-based distributed mutual
       exclusion algorithms that support the SLA concept. The first one is a modified version of the priority-based Kanrar-


                IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
                           Elysium Technologies Private Limited
                            Approved by ISO 9001:2008 and AICTE for SKP Training
                           Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
                           http://www.elysiumtechnologies.com, info@elysiumtechnologies.com

       Chaki algorithm [1] while the second one is a novel algorithm, based on Raymond algorithm [2], where a deadline is
       associated with every request. In both cases, our aim is to improve Critical Section execution rate and to reduce the
       number of SLA violations, which, for the first algorithm represents the number of priority inversions (i.e. a higher priority
       request is satisfied after a lower one) and for the second one, the number of requests whose deadline is not respected.
       Performance evaluation results show that our solutions significantly reduce SLA violations avoiding message overhead.


EGC
        SLA-based Optimization of Power and Migration Cost in Cloud Computing
3225



       Cloud computing systems (or hosting datacenters) have attracted a lot of attention in recent years. Utility computing,
       reliable data storage, and infrastructure-independent computing are example applications of such systems. Electrical
       energy cost of a cloud computing system is a strong function of the consolidation and migration techniques used to
       assign incoming clients to existing servers. Moreover, each client typically has a service level agreement (SLA), which
       specifies constraints on performance and/or quality of service that it receives from the system. These constraints result
       in a basic trade-off between the total energy cost and client satisfaction in the system. In this paper, a resource
       allocation problem is considered that aims to minimize the total energy cost of cloud computing system while meeting
       the specified client-level SLAs in a probabilistic sense. The cloud computing system pays penalty for the percentage of
       a client's requests that do not meet a specified upper bound on their service time. An efficient heuristic algorithm based
       on convex optimization and dynamic programming is presented to solve the aforesaid resource allocation problem.
       Simulation results demonstrate the effectiveness of the proposed algorithm compared to previous work.



EGC     Snooze: A Scalable and Autonomic Virtual Machine Management Framework for Private
3226
        Clouds

       With the advent of cloud computing and the need to satisfy growing customers resource demands, cloud providers now
       operate increasing amounts of large data centers. In order to ease the creation of private clouds, several open-source
       Infrastructure-as-a-Service (IaaS) cloud management frameworks (e.g. Open Nebula, Nimbus, Eucalyptus, Open Stack)
       have been proposed. However, all these systems are either highly centralized or have limited fault tolerance support.
       Consequently, they all share common drawbacks: scalability is limited by a single master node and Single Point of
       Failure (SPOF). In this paper, we present the design, implementation and evaluation of a novel scalable and autonomic
       (i.e. self-organizing and healing) virtual machine (VM) management framework called Snooze. For scalability the system
       utilizes a self-organizing hierarchical architecture and performs distributed VM management. Moreover, fault tolerance is
       provided at all levels of the hierarchy, thus allowing the system to self-heal in case of failures. Our evaluation conducted
       on 144 physical machines of the Grid'5000 experimental test bed shows that the fault tolerance features of the
       framework do not impact application performance. Moreover, negligible cost is involved in performing distributed VM
       management and the system remains highly scalable with increasing amounts of resources.




                IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
                            Elysium Technologies Private Limited
                            Approved by ISO 9001:2008 and AICTE for SKP Training
                            Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
                            http://www.elysiumtechnologies.com, info@elysiumtechnologies.com


 EGC     Taking up autonomous SOA framework into cloud computing
 3227



        Cloud computing is an extension of Service Oriented Architecture (SOA). For cloud elastic nature, it will often need to
        dynamically reconfiguring and reorganising the services interaction as some unpredictable events, such as crashes or
        network problems, will typically cause service unavailability. The complexity and dynamism of current global network
        system require an architecture that is capable of autonomously changing its structure and functionality to meet the
        changes with little human intervention. In this paper, an autonomic SOA framework is proposed to extend the
        intelligence and capability in the cloud. The use of case-based reasoning and the architectural consideration of
        autonomic computing paradigm are presented.


EGC
         THEMIS: A Mutually Verifiable Billing System for the Cloud Computing Environment
3228


        With the widespread adoption of cloud computing, the ability to record and account for the usage of cloud resources in
        a credible and verifiable way has become critical for cloud service providers and users alike. The success of such a
        billing system depends on several factors: the billing transactions must have integrity and nonrepudiation capabilities;
        the billing transactions must have a minimal computation cost; and the SLA monitoring should be provided in a trusted
        manner. Existing billing systems are limited in terms of security capabilities or computational overhead. In this paper,
        we propose a secure and nonobstructive billing system called THEMIS as a remedy for these limitations. The system
        uses a novel concept of a cloud notary authority for the supervision of billing. It generates mutually verifiable binding
        information that can be used to resolve future disputes between a user and a cloud service provider in a computationally
        efficient way. Furthermore, to provide a forgery-resistive SLA monitoring mechanism, we devised a SLA monitoring
        module enhanced with a trusted platform module (TPM), called S-Mon. This work has been undertaken on a real cloud
        computing service called iCubeCloud.


EGC
        Toward Secure and Dependable Storage Services in Cloud Computing
3229


        Cloud storage enables users to remotely store their data and enjoy the on-demand high quality cloud applications
        without the burden of local hardware and software management. Though the benefits are clear, such a service is also
        relinquishing users' physical possession of their outsourced data, which inevitably poses new security risks toward the
        correctness of the data in cloud. In order to address this new problem and further achieve a secure and dependable
        cloud storage service, we propose in this paper a flexible distributed storage integrity auditing mechanism, utilizing the
        homomorphic token and distributed erasure-coded data. The proposed design allows users to audit the cloud storage
        with very lightweight communication and computation cost. The auditing result not only ensures strong cloud storage
        correctness guarantee, but also simultaneously achieves fast data error localization, i.e., the identification of
        misbehaving server. Considering the cloud data are dynamic in nature, the proposed design further supports secure and


                 IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects
                           Elysium Technologies Private Limited
                           Approved by ISO 9001:2008 and AICTE for SKP Training
                           Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
                           http://www.elysiumtechnologies.com, info@elysiumtechnologies.com

       efficient dynamic operations on outsourced data, including block modification, deletion, and append. Analysis shows
       the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and
       even server colluding attacks.


EGC     Towards Trusted Services: Result Verification Schemes for MapReduce
3230


       Recent development in Internet-scale data applications and services, combined with the proliferation of cloud
       computing, has created a new computing model for data intensive computing best characterized by the MapReduce
       paradigm. The MapReduce computing paradigm, pioneered by Google in its Internet search application, is an
       architectural and programming model for efficiently processing massive amount of raw unstructured data. With the
       availability of the open source Hadoop tools, applications built based on the MapReduce computing model are rapidly
       growing. In this work, we focus on a unique security concern on the MapReduce architecture. Given the potential
       security risks from lazy or malicious servers involved in a MapReduce task, we design efficient and innovative
       mechanisms for detecting cheating services under the MapReduce environment based on watermark injection and
       random sampling methods. The new detection schemes are expected to significantly reduce the cost of verification
       overhead. Finally, extensive analytical and experimental evaluation confirms the effectiveness of our schemes in
       MapReduce result verification.



EGC     Video analysis tools for cloud-based motion detection
3230


       We present a fast moving object detection application by extending the functionality of open source tools that are
       available freely on the Internet. This application can be placed on a cloud infrastructure and performs fast processing so
       that the costs needed to use the cloud resources can be minimized.




                IEEE Final Year Projects 2012 |Student Projects | Cloud Computing Projects

				
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