Research Paper GRAPH AND SINR BASED INTERFERENCE MODELING AND ROUTING IN MANET Balamurugan.N.M, Appavu Alias Balamurugan.S

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1 Research Paper GRAPH AND SINR BASED INTERFERENCE MODELING AND ROUTING IN MANET Balamurugan.N.M, Appavu Alias Balamurugan.S Address for Correspondence CSE Department, Sri Venkateswara College of Engineering, Sriperumbudur, India IT Department, KLN College of information Technology, Sivagangai, India ABSTRACT Interference is a basic issue in wireless communication as it results in packet delay, retransmission and packet loss. By providing interference awareness to important functions such as routing helps in the enhancement of overall network performance as it avoids packet loss. Most of the existing systems capture the interference effects by active probing ie., measuring the effects of interference by periodically sending small active probe packets over the network. Hence, it causes additional overhead in the network and the link quality is perverted due to their interaction with other networking functions. To overcome this, an analytical model is designed to measure the interference effects on data delivery probability based on the passive measurement ie., information which is locally available at the node works similar to active probing. In the proposed work, the interference is modeled using interference graph method and physical interference model is used to arrive with an optimal routing metric based on the information locally available at the node and to incorporate in the routing protocol. Thus, the path with less or no interference is selected for routing. KEYWORDS- interference, physical interference model, Signal to interference ratio, interference graph model. I. INTRODUCTION Mobile Ad Hoc Networks (MANETs) are wireless, self-configuring networks of mobile devices. MANETs provides an autonomous system such that each device in the network independently moves in any direction and changes its links to other devices often and the network topology changes frequently. Thus, Routing protocols used in conventional wired networks cannot be used in ad hoc wireless networks due to their highly dynamic topology, absence of infrastructure, bandwidthconstrained wireless links and energy constrained nodes. In MANET, routing protocols are divided into two major categories based on the routing information and update mechanism: Table-driven routing protocols are the extension of wired network routing protocols. They are also called as proactive routing protocols. Every node maintains a global network topology in the form of routing tables by periodically exchanging the information and the tables are updated frequently. DSDV, CGSR are some examples of proactive protocols. On-demand routing protocols do not maintain the network topology information. On-demand routing protocols are also called as Reactive routing protocols. They obtain the necessary path information only when required (on-demand), by route discovery process and sends route error message and re-establishes the path in case of node movement, link failure, or path break occurs called as route maintenance process. AODV, DSR are some examples of Reactive routing protocols. Interference is the major limiting factor in the performance of mobile ad hoc networks (MANET). The two main forms of interference are adjacent channel and co-channel interference. Spectral resource reuse is a key feature of wireless networks as it increases the system capacity and gives raise to interference which leads to packet delay, retransmission, collision, packet loss. Thus, the simultaneous transmission of nodes which belong to the same channel causes Co-channel interference. Hence, interference model is necessary for ad hoc networks since it has dynamic topology and lack of central co-ordination. Interference models are divided into three categories such as statistical interference models, models that describe the effects of interference and graph based interference models. Statistical interference models involve the statistical characterization of the aggregate interference and are expressed in terms of probability density function or moments. Thus the probability that Signal to Interference ratio at receiver is greater than the minimum threshold value for successful communication. Thus the aggregate interference is the incoherent sum of individual interfering signals. Modeling the effects of interference relies on the performance or behavior of the network which is affected by interference. Two popular models which model the effect of interference are protocol interference model and physical interference model. Protocol interference model describes a pair-wise interference relationship between two terminals or links. Physical Interference Model focuses on the effects of the aggregate interference observed by the receiver, due to all other transmitters. A wireless network can be modeled by means of Graph based on their connection called as connectivity graph G=(V,E). Graphs can also be used to model the interference in the network, which is called as interference graph which is denoted as GI= (V I, E I ), and it contains two forms: (1) graphs that model interference between terminals (2) graphs that model interference between links. Thus, the network performance can be enhanced by reducing the interference. In the proposed work, interference is modeled using interference graph method and Physical interference model. Using interference model, average SIR value is derived and is used as a routing metric. Based on the routing metric and graph based interference model, less interference path or no interference path is selected for routing which is used to enhance the performance of routing protocol and also improves the overall performance of the network. II. RELATED WORK A number of interference modeling techniques and metrics have been proposed for estimating the effects of interference in the wireless networks. H. Venkataraman et al, (2007) in [5], analyzed the effects of spatial margin on the performance of multi-hop networks using the protocol interference model. Here, a Spatial protection region is a circular exclusion region which is specified around all receiving nodes so that only the intended transmitter is allowed to reuse the same frequency resource

2 within that region and the system throughput is high when the value of spatial protection margin is nearly unity. Thus for bounded network area, the frequency reuse efficiency is high when the protection margin is around unity. Increased spatial margin results in the reduction in the number of simultaneously communicating pairs which results in the decrease of amount of interference experienced by any receiver. Kortebi R M and NazimAgoulmine (2007) in [6], proposed a new routing metric called EBC (Estimated balanced capacity) to achieve loadbalancing among the different flows. In this method, 2-hop interference estimation algorithm (2-HEAR) is proposed based on the measurement of the received signal strength. Based on the received signal strength, SINR value is calculated using Physical interference model. SINR value is used to infer the packet error rate (PER). Based on PER, the capacity at a given node is estimated and a new metric called Estimated Balanced Capacity (EBC) is proposed in order to achieve load-balancing among the different flows. Kamal Jain and VenkatPadmanabhan (2003) in [7], proposed a model and methodology for computing bounds on the optimal throughput for multi-hop wireless network. Conflict graph is used to model the effects wireless interference. The conflict graph comprises of the group of mutually interfering links which cannot be active simultaneously based on physical interference model and protocol interference model. Conflict graphs are used to find the upper bound whereas independent sets are used to represent the lower bound. The optimal solution is obtained when upper and lower bounds are equal. Based on the bounds packet transmissions are carefully scheduled to avoid interference for a given set of source and destination Daniel Aguayo and John Bicket (2005) in [3], proposed the expected transmission count metric (ETX), which finds high-throughput path on multihop wireless network. The performance of ETX metric is measured by using with DSDV and DSR routing protocol. ETX metric is calculated based on the forward and reverse delivery ratio. The forward delivery ratio is the probability of successful delivery of data packet at the recipient and the reverse delivery ratio is the probability of successful delivery of acknowledgement packet at the sender. The ETX of a link is the estimated number of transmissions and retransmissions required to send a packet over the link. ETX reduces the expected number of transmissions and retransmissions required for the successful delivery of data packet. Richard Draves and Brain Zill (2004) in [9], proposed a new metric for routing in multi-radio, multi-hop wireless networks. The goal of the metric is to reduce the intra-flow interference ie., to reduce the number of nodes on the path of flow that transmit on the same channel and to choose a high throughput path between the source and the destination. Weight is assigned to each link based on the Expected Transmission Time (ETT) of a packet over that link. ETT is the combination of ETX (number of expected transmissions) and it is a function of the loss rate and the bandwidth of the link. The weight of individual links are combined to form a path metric called Weighted Cumulative ETT (WCETT) specifies the interference among links using the same channel and it is used along with LQSR (Link-Quality Source Routing) routing protocol called as MR-LQSR (Multi-Radio Link-Quality Source Routing). Xinming Zhang et. al., (2007) in [11], proposed a new routing protocol called Average link interference-aware routing protocol (ALIR). The interference area is divided into three parts such as area with highest interference ie., closest area of the node, moderate and less interference. Based on this, weight is obtained to represent different interference and assumed that the interference range is 3times transmission range and the average interference value for path is calculated. Thus, this protocol selects the path with minimum average link-interference among optional paths between the source and destination. Hence, this not only helps to reduce collisions and packet retransmissions, but also saves energy, resulting in higher throughput and better performance. Yaling Yang et. al, (2005) in [12], proposed a new metric MIC(Metric of Interference and Channel switching), and a novel routing scheme, called LIBRA (Load and Interference Balanced Routing Algorithm), to provide interference aware and multichannel/multi-radio aware load balancing for mesh networks. Metric of Interference and Channel switching is the combination of Interference Resource Usage (IRU) and CSC (Channel Switching Cost) where IRU represents the inter-flow interference and is a combination of ETT (Expected Transmission Time). CSC represents the intra-flow interference and is aimed at decreasing the delay and increasing the throughput of individual flows. By using Bellman-Ford or Dijkstra s algorithm on the network, LIBRA can calculate minimum MIC weight paths of the real network so that flows can be routed though minimum weight paths and no forwarding loops are created for either distance-vector or linkstate routing. Hence, there are many interference-aware routing metric, modeling techniques are proposed to reduce the interference. The main goal of our work is to model the interference by passive measurements using Physical interference model and Graph-based interference method. Fig.1. The proposed work III. PROBLEM FORMULATION The main problem in this paper deals with modeling the interference in mobile ad hoc network by using Physical interference model and Graph based interference model. The proposed interference model focuses on modeling interference and routing packets in the no interference path or less interference path.

3 IV. PROPOSED SYSTEM The main goal of our work is to model the interference using physical and graph-based interference model. The outline of proposed method is illustrated in Figure 1. The possible routes are obtained from source to destination using DSR routing protocol. Physical interference model is used to calculate the aggregate interference and the signalto-interference ratio is calculated. The average signalto-interference ratio of the path is used as a routing metric and rated. Using the Graph-based interference model, concurrently active links are obtained for each link in the path. The number of concurrently active links for each link in the path is estimated and rated. Thus, the rated path based on the Physical interference model and Graph-based interference model are compared and selected for routing using DSR protocol and performance evaluation of DSR protocol is done. A. Physical interference model Consider the edge e= (t, r)which represents transmitter tand receiver r.let i ϵ I be the set of interferers around the receiver. Consider all nodes in the network has uniform transmitter power, the SIR value for a node is obtained as, SIR(e) (D D ) = (1) iϵi (D D ) where (D t -D r ), (D i -D r ) is the transmitter-receiver and interferer receiverdistance repsectively and α is the path loss exponent. Thus, communication between the transmitter and receiver node is successful only if SIR, where is the minimum threshold required for the successful delivery of packet. SIR for the path p where e ϵ p is obtained as the summation SIR value for each node in the path, SIR(p) = SIR(e) (2) Average SIR value for the path is obtained as follows, Metric(p) = SIR(p) (3) n Here, n is the number of links belonging to that path which represents the overall length of the path. The routing protocol records the SIR value of each node and computes the SIR value of the link related. When the Route-request packet reach the destination node, the SIR value for the whole path is obtained and the average SIR value is computed for the whole path. When receiving the Route-reply packet, the source node records the average SIR value for each path. Thus, the path with maximum average SIR value is rated. B. Graph based interference model Consider a graph G= (V,E), where V represents the set ofvertices and E represents the set of edges joining two vertices makes them appropriate for modeling wireless networks. Graphs which are used to model the interference in network are called as Interference graph. Interference graphs are represented as G I =(V I,E I ). There are two types of interference graphs such as (i) graphs which represent the interference between terminals and (ii) graphs which represent the interference between links. Consider a network with transmitter receiver pair (x, y) with distance rassociated with an interference disk of radius r i (y) = r β 1/η centered at y, inside which no active transmitter can be present in order to provide the successful delivery at receiver. Thus, interference disk is link specific and are used to construct the interference graph to model the interference among links. Fig.2. Connectivity Graph G= (V,E) Consider the connectivity graph shown in Figure 2 in which all terminals transmit at same power with an interference range,r i and D(x, r i (x)) represents the interference disk of receiver x. Fig.3. Interference Graph G I = (V I,E I ) The resulting interference graph for the Figure 2 is shown in Figure 3 in which the link l tx interferes with the link l sw but not vice versa since the transmitter t falls within the interference range of receiver w. Therefore, the links l sw and l tx should not be simultaneously active but the link l uy can be simultaneously active with either l sw or l tx. Similarly, the link l vz interferes with the link l uy but not vice versa since the transmitter v falls within the interference range of receiver y. Therefore, the links l uy and l vz should not be simultaneously active but the link l vz can be simultaneously active with either l sw or l tx. Protocol interference model is based on the vulnerability circle capture model which describes a pair-wise interference relationship between two terminals or links Hence, Protocol interference model is appropriate for constructing graphs which represents the interference relationship between two terminals or links and defines the condition for successful communication over a given link. Consider the Figure 4 in which the communication takes place over the link (T i,r i )with the interference region Iiaround the receiver R i and the pair (T k,r k ) be another link on the same channel. Fig.4. Protocol Interference model Communication over link (T i,r i ) is successful only if the distance between the receiver and any other terminal T k is larger than the distance between T k and R k by a factor (1+ ), > (1 + ) (5)

4 where D ti D ri represents the distance between terminals T i and R i, represents the constant which is greater than zero. Equation (5) suggests that T i requires an interferer-free circular zone around R i for successful reception at receiver R i. In other words, communication over link (Ti,R i ) is successful if, (1 + ) (6) Thus (6), suggests that successful transmissions require non-overlapping circular regions around the receiversr i and R k. Consider two active links (T i,r i ), (T k,r k ) in which both transmission based on (5) and (6) will be successful if, > 2 ( + ) (7) Based on (7), simultaneously active linkscan be formed. The figure 5 shows the concurrently active links for the link l sw. Packet delivery ratio is defined as the ratio of total number of packets reached at the destination node to that of number of packets generated by the source. Pause time of a node (rest time) refers to certain amount of time at which the node stays at a fixed location without movement. The node pauses for a particular period of time after which starts to move to a random place (destination). The simulation result in figure 6, pause time (sec) versus packet delivery ratio shows that the packet delivery ratio is higher for Interference aware AODV routing protocol when compared to AODV routing protocol. Thus, the successful delivery of packet to the destination of IA- AODV routing protocol is high when compared to the AODV routing protocol. Fig.5. Construction of concurrent links The link l sw can simultaneously active with either link l uy or l vz. Similarly, the concurrently activelinks(noninterfering links) and interfering links for every link in the path is estimated. The total number of concurrently active links for each path is calculated. Thus, the path with maximum number of concurrently active links is obtained and rated. Thus table 1, shows the non-interfering and interfering links of figure 2. Table I Link schedule Synchronized links l ab, l fe l ij, l ab l fe, l cd l op, l ij l ij, l mn l fe, l mn l kl, l gh l kl, l ab l kl, l cd Asynchronized links l ab, l cd l ab, l gh l gh, l ij l kl, l mn l mn, l op l gh, l cd Thus, the path with maximum average SIR value and the path with maximum number of concurrently active links are compared and selected for routing as both methods suggest the path with less interference. Hence, this method helps to improve the performance of DSR routing protocol. V. SIMULATION RESULTS The nodes are randomly placed in m2 region. Nodes are placed under wireless channel with dynamic network propagates with Two ray ground model. Each node is supported with omni-directional antenna and the propagation model used here is Two ray ground model with the path loss exponent value 4, (α=4). Thus table 2 shows simulation parameters used. Table II:Simulation Parameters Parameters Values Data CBR Traffic Propagation model Two ray Ground Antenna Omni-Antenna Routing Protocol AODV Packet Size 512 Bytes Fig. 6. Packet Delivery ratio Vs Pause time (sec) Packet rate refers to the total number of outgoing packets from the network. End-to-End delay refers to the time taken for a packet to reach the destination node from the source node. The simulation result in figure 7, packet rate (packets/sec) versus end-to-end delay shows that end-to-end delay of IA-AODV routing protocol is less than the AODV routing protocol. Thus the simulation result shows that providing interference awareness to routing protocol reduces the packet loss, delay and improves the successful delivery ratio of the packet and at the same time it also enhances the overall performance of the entire network. Fig. 7. End-to-End Delay Vs Packet rate(packet/sec) VI. CONCLUSION Modeling the interference in wireless ad hoc networks is the main aim of the proposed work. Thus, interference is modeled using physical and graph based interference model and the path with less interference is selected for routing. Thus, providing interference awareness to routing function increases the packet delivery ratio and throughput which in turn improves the overall network performance. The future work is to model the interference in active research areas which include the complex scenarios like Wireless Sensor networks is essential.

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