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                                                                IJART, Vol. 2 Issue 1, 2012,58-62

                                                                      ISSN NO: 6602 3127


Jamming Aware Energy Efficient Multicast Routing
         In Mobile ADHOC Networks
                   D.Jayachandran,II ME CSE,The Kavery Engineering College.
                       A.Prabhu,AP/CSE,The Kavery Engineering College.


Multiple-path source routing protocols allow a data source node to distribute the total traffic among available
paths. In this article, 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 multi-source 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
Index terms: Wireless network, security, routing, node capture attack, HTTPS


A mobile Ad hoc network (MANET) is a collection of       each other, communication over rugged terrain –
autonomous mobile nodes capable of communicating         where establishing infrastructure is not cost effective.
with each other via wireless links. Nodes in a           Ad hoc networks can also be used to deploy
MANET        have    limited    transmission range;      multimedia services; however efficient routing
communication is achieved by making use of nodes to      protocols have to be developed before this can be
forward packets to other nodes, which thereby have to    realized.The high node mobility, low bandwidth
operate as routers. Finding a path between two           wireless interfaces, limited battery power and
communication end points in an ad hoc network is         contention for a shared wireless medium makes
non trivial: node mobility results in highly dynamic     designing routing protocols for ad hoc networks
network topologies. These networks are rapidly           difficult; any new routing protocol must take note of
deployable, as they do not require any infrastructure    these factors critically.
in place. MANETs are highly desirable in a variety of    Several routing protocols have been proposed in ad
scenarios: disaster recovery-where the entire            hoc networks. But none are proposed with security.
communication infrastructure might have been             Our project addresses location aided routing with
destroyed, business meetings- where a group of           security.
people have to share resources and communicate with

ISSN NO: 6602 3127                                                       Page | 58
                              International Journal of Advanced Research in Technology Vol. 2 Issue 1, March 2012

                                                                    the source nodes using a distributed
2. RELATED WORK                                                     algorithm based on decomposition in
                                                                    network utility maximization (NUM) [14].
                                                                    Propose methods which allow individual
PAMAS protocol that uses two different channels to
                                                                    network nodes to locally characterize the
separate data and signaling. The Suresh Singh, Mike
                                                                    jamming impact and aggregate this
Woo and C.S. Raghavendra presented several power-
                                                                    information for the source nodes.
aware metrics that do result in energy-efficient routes.
                                                                    Demonstrate that the use of portfolio
The Minimum Total Transmission Power Routing
                                                                    selection theory allows the data sources to
(MTPR) was initially developed to minimize the total
                                                                    balance the expected data throughput with
transmission power consumption of nodes
                                                                    the uncertainty in achievable traffic rates.
participating in the acquired route. The Min-Max
Battery Cost Routing (MMBCR) considers the
remaining power of nodes as the metric for acquiring       4. SYSTEM MODEL AND ASSUMPTIONS
routes in order to prolong the lifetime of network.
C.K.Toh presented the Conditional Max-Min Battery          4.1 Network Model
Capacity Routing (CMMBCR) protocol, which is a
hybrid protocol that tries to arbitrate between the        The wireless network of interest can be represented by
MTPR and the MMBCR. The several multipath                  a directed graph G = (N, E). The vertex set N
proactive routing protocols were developed. These          represents the network nodes, and an ordered pair (i,
protocols use table-driven algorithms (link state or       j) of nodes is in the edge set E if and only if node j
distance vector) to compute multiple routes. But they      can receive packets directly from node i. We assume
do not consider the power aware metrics and these          that all communication is unicast over the directed
protocols generate excessive routing overhead and          edges in E, i.e. each packet transmitted by node i ! N
perform poorly because of their proactive nature. The      is intended for a unique node j ! N with (i, j) ! E. The
on-demand routing is the most popular approach in          maximum achievable data rate, or capacity, of each
the MANET. Instead of periodically exchanging route        unicast link (i, j) ! E in the absence of jamming is
messages to maintain a permanent route table of the        denoted by the pre predetermined constant rate cij in
full topology, the on- demand routing protocols build      units of packets per second. Each source node s in a
routes only when a node needs to send the data             subset S " N generates data for a single destination
packets to a destination. The standard protocols of this   node ds ! N. We assume that each source node s
type are the Dynamic Source Routing (DSR) routing.         constructs multiple routing paths to ds using a route
However, these protocols do not support multipath.         request process similar to those of the DSR [9] or
The several multipath on- demand routing protocols         AODV [10] protocols. We let Ps = {ps1, . . . , ps Ls}
were proposed. Some of the standard protocols are the      denote the collection of Ls loop-free routing paths for
Ad hoc On- demand Multipath Distance Vector                source s, noting that these paths need not be disjoint
(AOMDV), the Split Multipath Routing (SMR), the            as in MP-DSR [11]. Representing each path ps! by a
Multipath Source Routing (MSR) [13], the Ad hoc            subset of directed link set E, the sub-network of
On-demand Distance Vector Multipath Routing                interest to source s is given by the directed subgraph.
(AODVM) and the Node- Disjoint Multipath Routing
(NDMR). These protocols build multiple routes based        5. OPTIMAL     JAMMING-AWARE
on demand but they did not consider the power aware           TRAFFIC ALLOCATION
                                                           In this section, we present an optimization framework
3. MY CONTRIBUTIONS                                        for jamming-aware traffic allocation to multiple
                                                           routing paths in Ps for each source node s ! S. We
The allocation of traffic across multiple routing paths.   develop a set of constraints imposed on traffic
My contributions to this problem are as follow:            allocation solutions and then formulate a utility
         Formulate the problem of allocating traffic       function for optimal traffic allocation by mapping the
         across multiple routing paths in the presence     problem to that of portfolio selection in finance.
         of jamming as a lossy network flow                Letting 's! denote the traffic rate allocated to path ps!
         optimization problem. We map the                  by the source node s, the problem of interest is thus
         optimization problem to that of asset             for each source s to determine the optimal Ls×1 rate
         allocation using portfolio selection theory       allocation vector "s subject to network flow capacity
         [12], [13].                                       constraints using the available statistics !s and !s of
         Formulate the centralized traffic allocation      the end-to-end packet success rates under jamming.
         problem for multiple source nodes as a
         convex optimization problem.
         Show that the multi-source multiple-path
         optimal traffic allocation can be computed at

ISSN NO: 6602 3127                                                          Page | 59
                               International Journal of Advanced Research in Technology Vol. 2 Issue 1, March 2012

5.1 Traffic Allocation Constraints                           to end delay and packet faction delivery varying
                                                             number of nodes, speed and time. Simulation results
In order to define a set of constraints for the multiple-    show that DSDV compared with AODV, DSDV
path traffic allocation problem, we must consider the        routing protocol consumes more bandwidth, because
source data rate constraints, the link capacity              of the frequent broadcasting of routing updates. While
constraints, and the reduction of traffic flow due to        the AODV is better than DSDV as it doesn’t maintain
jamming at intermediate nodes. The traffic rate              any routing tables at nodes which results in less
allocation vector "s is trivially constrained to the         overhead and more bandwidth. AODV perform better
nonnegative orthant, i.e. "s * 0, as traffic rates are       under high mobility simulations than DSDV. High
non-negative.                                                mobility results in frequent link failures and the
                                                             overhead involved in updating all the nodes with the
5.2 Optimal Traffic Allocation Using Portfolio               new routing information as in DSDV is much more
Selection Theory                                             than that involved AODV, where the routes are
                                                             created as and when required. AODV use on -demand
In order to determine the optimal allocation of traffic      route discovery, but with different routing
to the paths in Ps, each source s chooses a utility          mechanisms. AODV uses routing tables, one route per
function Us("s) that evaluates the total data rate, or       destination, and destination sequence numbers, a
throughput, successfully delivered to the destination        mechanism to prevent loops and to determine
node ds. In defining our utility function Us("s), we         freshness of routes.When a source node wants to send
present an analogy between traffic allocation to             packets to a destination to which it does not have a
routing paths and allocation of funds to correlated          route, it initiates a Route Discovery by broadcasting a
assets in finance. In Markowitz’s portfolio selection        ROUTE REQUEST. The node receiving a ROUTE
theory [12], [13], an investor is interested in allocating   REQUEST checks whether it has a route to the
funds to a set of financial assets that have uncertain       destination in its cache and also check if it is
future performance. The expected performance of              misbehavior node or not. If it has, it sends a ROUTE
each investment at the time of the initial allocation is     REPLY to the source including a source route, which
expressed in terms of return and risk. The return on         is the concatenation of the source route in the ROUTE
the asset corresponds to the value of the asset and          REQUEST and the cached route. If the node does not
measures the growth of the investment. The risk of the       have a cached route to the destination, it adds its
asset corresponds to the variance in the value of the        address to the source route and rebroadcasts the
asset and measures the degree of variation or                ROUTE REQUEST. When the destination receives
uncertainty in the investment’s growth. Describe the         the ROUTE REQUEST, it sends a ROUTE REPLY
desired analogy by mapping this allocation of funds to       containing the source route to the source. Each node
financial assets to the allocation of traffic to routing     forwarding a ROUTE REPLY stores the route starting
paths.We relate the expected investment return on the        from itself to the destination. When the source
financial portfolio to the estimated end-to-end success      receives the ROUTE REPLY, it caches the source
rates !s and the investment risk of the portfolio to the     route. If any node not sends acknowledgement then
estimated success rate covariance matrix !s. We note         we easily identified that is misbehavior node. So find
that the correlation between related assets in the           out the alternative path and forwarding the data to the
financial portfolio corresponds to the correlation           destination.The Message transfer relates with that the
between non-disjoint routing paths. The analogy              sender node wants to send a message to the
between financial portfolio selection and the                destination node after the path is selected also find out
allocation of traffic to routing paths is summarized         that node is not a misbehavior node and status of the
below.                                                       destination node through is true. The receiver node
                                                             receives the message completely and then it send the
                                                             acknowledgement to the sender node also nearby
6. AODV AND DSDV                       PROTOCOL
                                                             nodes through the router nodes where it is received
   IMPLEMENTATION                                            the message.
Wireless networks are characterized by a lack of             7. Simulation Result and Simulation Setup
infrastructure, and by a random and quickly changing
                                                             Platform                   Windows XP
network topology; thus the need for a robust dynamic
                                                             Java Sim                   Jist
routing protocol that can accommodate such an
                                                             Pause time                 0, 20, 40, 80, 120, 160,
environment. To improve the packet delivery ratio of
Destination-Sequenced Distance Vector (DSDV)
routing protocol in mobile ad hoc networks with high         Simulation time            200 s
mobility, a message exchange scheme for its invalid          Number of nodes            50 wireless nodes
route reconstruction is being used. Two protocols            Traffic                    CBR(Constant         Bit
AODV and DSDV simulated using Java simulation                                           Rate)
package and were compared in terms throughput, end           Simulation Area size       500 x 500 m
                                                             Transmission Range         250 m

ISSN NO: 6602 3127                                                            Page | 60
                               International Journal of Advanced Research in Technology Vol. 2 Issue 1, March 2012

The following metrics are used in this paper for the
analysis of AODV, DSR and DSDV routing

i) Packet Delivery Ratio
ii) Average End to End Delay
iii) Throughout

Packet delivery ratio The packet delivery ratio in
this simulation is defined as the ratio between the
number of packets sent by constant bit rate sources
(CBR, ”application layer”) and the number of               Figure3. Avg. end to end delay versus pause time
received packets by the CBR sink at destination.           for AODV, DSR and DSDV (Number of node = 50,
                                                           Area space = 500m x 500m)
Routing Overhead It is the number of packet
generated by routing protocol during the simulation.       7. CONCLUSION AND FUTURE WORK
Average end-to-end delay of data packets                   In this paper the analysis of adhoc routing protocol is
There are possible delays caused by buffering during       done in the above mentioned mobility and traffic
route discovery latency, queuing at the interface          pattern on different pause time. We analyzed that
queue, retransmission delays at the MAC, and               when pause time set to 0 each of the routing protocols
propagation and transfer times. Once the time              obtained around 97% to 99% for packet delivery ratio
difference between every CBR packet sent and               except DSDV which obtained 77%. DSR and AODV
received was recorded, dividing the total time             reached approx 100% packet delivery ratio when
difference over the total number of CBR packets            pause time equal to 200 while DSDV obtained only
received gave the average end-to-end delay for the         approx 94% packet delivery ratio.
received packets. This metric describes the packet
delivery time: the lower the end-to-end delay the          DSR and DSDV has low and stable routing overhead
better the application performance.                        as comparison to AODV that varies a lot. Avg. End to
                                                           End delay of DSDV is very high for pause time 0 but
                                                           it starts decreasing as pause time increases. DSR
                                                           performs well as having low end to end delay. When
                                                           we compare the three protocols in the analyzed
                                                           scenario we found that overall performance of DSR is
                                                           better than other two routing protocols.

                                                           DSDV routing protocol consumes more bandwidth,
                                                           because of the frequent broadcasting of routing
                                                           updates. While the AODV is better than DSDV as it
                                                           doesn’t maintain any routing tables at nodes which
                                                           results in less overhead and more bandwidth. From
                                                           the above, chapters, it can be assumed that DSDV
Figure1. Packet delivery ratio versus pause time           routing protocols works better for smaller networks
for AODV, DSR and DSDV(Number of node = 50,                but not for larger networks. So, my conclusion is that,
Area space = 500m x 500m)                                  AODV routing protocol is best suited for general
                                                           mobile ad-hoc networks as it consumes less
                                                           bandwidth and lower overhead when compared with
                                                           DSDV routing protocol. AODV perform better under
                                                           high mobility simulations than DSDV. High mobility
                                                           results in frequent link failures and the overhead
                                                           involved in updating all the nodes with the new
                                                           routing information as in DSDV is much more than
                                                           that involved AODV, where the routes are created as
                                                           and when required. AODV use on - demand route
                                                           discovery, but with different routing mechanics.
                                                           AODV uses routing tables, one route per destination,
Figure2. Routing overhead versus pause time for            and destination sequence numbers, a mechanism to
AODV, DSR and DSDV (Number of node = 50,                   prevent loops and to determine freshness of routes.
Area space = 500m x 500m)

ISSN NO: 6602 3127                                                        Page | 61
                            International Journal of Advanced Research in Technology Vol. 2 Issue 1, March 2012

Future work of this project We present a family of
energy-conserving flooding protocols capable of
supporting both reactive and proactive routing
approaches, as well as network applications that rely
on flooding. Based on realistic simulation models,
these protocols show significant energy-conserving
potential. Future work will focus on methods for
balancing the protocols’ overhead and relay
optimality to further enhance their efficiency.

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ISSN NO: 6602 3127                                                     Page | 62

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