Research Paper GNANAMANOHARAN ET AL., INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING TECHNOLOGY E-ISSN

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1 Research Paper PERFORMANCE ANALYSIS OF PROBABILISTIC BROADCAST ON DEMAND ROUTE DISCOVERY PROTOCOL FOR MOBILE AD HOC NETWORKS BASED ON NODE MOBILITY E.Gnanamanoharan 1, R.Bensraj 2 Address for Correspondence 1 Assistant Professor, 2 Professor, Department of Electrical Engineering, Annamalai University, Annamalainagar , India. ABSTRACT A mobile ad hoc network (MANET) enables wireless communications between participating mobile nodes without centralized administration. Two nodes that are out of one another s transmission range need the support of intermediate nodes, which relay messages to set up a communication between each other. The broadcast operation is the most fundamental role in MANETs. In on-demand route discovery, Simple flooding is widely used, where each node blindly rebroadcast the received RREQ till appropriate route to destination is accomplished Where each node forwards the packet once and only once, makes every node a forwarding node. If the forwarding nodes are not carefully designated, they will trigger many retransmissions at the same time, which might congest the network. It aggravates a high number of unnecessary packet rebroadcasts, causing contention, packet collisions and broadcast storm problem, which has been shown to greatly increase the network communication overhead and end-to-end delay. The performance degradation of such problems can be reduced if measures are taken during the dissemination of RREQ packets. Efficient broadcasting method can reduce the number of rebroadcasting, therefore reduce the chance of contention and minimize the collision among neighbouring nodes. We introduce a new probabilistic approach for route discovery, that is simple to implement and can significantly reduce the overhead related with the dissemination of RREQs. Simulation results shows this on demand probabilistic route discovery performs well and can result in significant reduction of control overhead while achieving increased throughput, packet delivery ratio and reduced delay compared with AODV and DSDV. KEYWORDS: Collision, Flooding, Forwarding Probability, MANETs, Network Connectivity, Reactive Routing overhead. 1. INTRODUCTION A MANET consists of randomly distributed nodes that result in some regions of the network being very dense and others being very sparse. One of the fundamental challenges in the design of MANETs in a multi-hop environment is the design of dynamic routing protocol that can efficiently establish routes to deliver data packets between mobile nodes with minimum communication overhead while ensuring high throughput and low end-to-end delay. Networkwide dissemination is used widely in MANETs [1] for the process of route invention, address resolution, and other network layer tasks. For example, on demand routing protocols such as ad hoc on demand distance vector (AODV) [8] and dynamic source routing (DSR) [13] use the broadcast information in route request packets to construct routing tables at every mobile node [4]. The lively nature of MANETs, however, requires the routing protocols to refresh the routing tables regularly, which could generate a large number of broadcasting Packets at various nodes. Since not every node in a MANET can communicate directly with the nodes outside its communication range, a broadcast packet may have to be rebroadcast several times at relaying nodes in order to guarantee that the packet can reach all nodes. Consequently, an inefficient broadcast approach may generate many redundant rebroadcast packets [5]. Fig. 1. Scenario for a Wireless Mobile Ad Hoc Network One approach to minimize the overhead is to establish routes on demand rather than proactively. On-demand routing protocols [9, 14, 2, 4, 12] only discover the route to a destination when it is necessary to send packets to that destination, and therefore incur less overhead and On-demand routing overhead can be broken down into two components: route discovery and route maintenance. When a source node first wishes to establish a route to a destination, it must search the network until it finds either the destination or another node which has a route to the destination. Many of the proposed protocols for ad hoc networks perform a flood-based route discovery, whereby a route request (RREQ) packet is flooded across the network which leads broadcast storm problem. Route discovery is determination of which route a packet should take from the transmitter to the receiver. Route discovery is typically done by means of control packets that are broadcast in the network, and record the quality of the links between different nodes. In order to achieve optimum performance, routing has to be changed whenever the link between nodes changes significantly. If a very low packet error rate is required, each node that acts as a relay stores the packets in a buffer and deletes them only after receiving an acknowledgment of successful transmission from the node it forwarded the packet to destination. In multi-hop MANETs where all the nodes may not be within the transmission range of the source, intermediate nodes may need to assist in the broadcast operation by retransmitting the packet to other remote nodes in the network. In traditional broadcast settings, the dissemination of packets often uses up valuable network resources such as node power and bandwidth. Flooding is a very expensive process that introduces lot of redundancy in the packet retransmission process. In [2], it has been observed that with flooding, when a node receives a packet for the first time, at least 39% of the node s neighbourhood would have also received the message simultaneously and on average only 41% of additional area could be covered with a rebroadcast. In general, when a node rebroadcasts a message after hearing it k times, the expected additional coverage decreases exponentially with increasing values of k

2 [2]. These observations motivated researchers to introduce several efficient broadcasting strategies that will minimize the number of redundant retransmissions and at the same time maximize the chances of the broadcasted message reaching all the nodes in the network. In this paper, a new route discovery method using AODV and rebroadcast probability of a host according to number of neighbour nodes information which addresses the broadcast storm problem in existing on-demand routing protocols. The rebroadcast probability would be low when the number of neighbour nodes are high which means host is in dense area and the probability would be high when the number of neighbour nodes are low which means host is in sparse area. Node mobility causes link states and the network topology to change frequently. 2. RELATED WORK The routing overhead associated with the dissemination of routing control packets such as RREQ packets can be quite huge, especially when the network density is high and the network topology frequently changes. Traditional on-demand routing protocols [3-5] produce a large amount of routing control traffic by blindly flooding the entire network with RREQ packets during route discovery. Recently, the issue of reducing the routing overhead associated with the route discovery and maintenance processes in on-demand routing protocols has attracted increasing attention. In [7] suggested Location Aided Routing (LAR) algorithm as an approach to mitigate the route discovery overhead by utilizing location aided information for mobile nodes. The Routing Ondemand Acyclic Multi-path (ROAM) [19] protocol mitigates the number of retransmissions of RREQ floods by using directed acyclic sub graphs based upon the distance between the source and destination nodes. Probabilistic routing approaches have also been proposed to help control the dissemination of the routing controls packets. probability value for nodes with fewer neighbours) are introduced to prevent broadcast packets from quickly dying out and/or prevent nodes from transmitting excessive packets. In this approach, the forwarding node uses its local density (i.e. number of neighbours) to decide the forwarding probability to be used by neighbours. As a consequence, the forwarding probability at a node is predetermined by its predecessor. 3. REVIEW OF BROADCASTING STRATEGIES In general, the broadcasting strategies can be grouped into four families: Simple flooding, Probability-based methods, Area-based methods and Neighbour knowledge based methods. 3.1 Simple Flooding The simplest method of broadcasting is flooding. In this technique, each node retransmit the RREQ when received for the first time. Packets that have already been received are just dropped. Flooding introduces a large number of redundant messages and leads to contention and collision which is referred to broadcast storm problem [3]. 3.2 Probability-based Methods Probabilistic Scheme In probability-based methods, each node is assigned a probability for retransmission. When a node receives a broadcast message for the first time, the node rebroadcasts the message with a probability P. For sparse networks, the value of P has to be high enough to facilitate a higher packet delivery ratio. When P = 1, the scheme resorts to simple flooding Counter-based Scheme A broadcast message received for the first time is not immediately retransmitted to the neighbourhood. The message is queued up for a time called the Random Assessment Delay (RAD) during which the node may receive the same message (redundant broadcasts) from some of its other neighbours. After the RAD timer expires, if the number of times the same message is received exceeds a counter threshold, the message is not retransmitted and is simply dropped. 3.3 Area-based Methods In area-based methods, a common transmission range is assumed and a node will rebroadcast if only sufficient new area can be covered with the retransmission Distance-based Scheme When a node receives a previously unseen broadcast message, the node computes the distance between itself and the sender. If the sender is closer than a threshold distance, the message is dropped. Otherwise, the received message is cached and the node initiates a RAD timer. Redundant broadcast messages received before the expiry of the RAD timer are also cached. When the RAD timer expires, the node computes the distance between itself and the neighbour nodes that previously broadcast the particular message. If any such neighbour node is closer than a threshold distance value, the message is dropped. Otherwise, the message is retransmitted. 3.4 Location-based Scheme Whenever a node originates or rebroadcasts a message, the node puts its location information in the message header. The receiver node calculates the additional coverage area that would be obtainable if it were to rebroadcast. If the additional coverage is less than a threshold value, all future receptions of the same message will be dropped. Otherwise, the RAD timer is started. Redundant broadcast messages received before the expiry of the RAD timer are also cached. After the RAD timer expires, the node considers all the cached messages and recalculates the additional obtainable coverage area if it were to rebroadcast the particular message. If the additional obtainable coverage area is less than a threshold value, the cached messages are dropped. Otherwise the message is rebroadcast. 3.5 Neighbour Knowledge based Methods In neighbour-knowledge based methods, each node stores neighbourhood state information and uses it to decide whether to retransmit or not Multi-point Relaying Under this scheme, each node is assumed to have a list of its 1-hop and 2-hop neighbours, obtained via periodic Hello beacons. The Hello messages include the identifier of the sending node, the list of the node s known neighbours and the Multi-Point Relays (MPRs). After receiving Hello messages from all its neighbours, a node has the 2-hop topology information centred at itself. Using this list of 1-hop and 2-hop neighbours, a node selects the MPRs the 1-hop neighbours that most efficiently reach all nodes within its 2-hop neighbourhood. Each node selects the set of MPRs using a greedy approach

3 of iteratively including the 1-hop neighbours that would cover the largest number of uncovered 2-hop neighbours Minimum Connected Dominating Set A Connected Dominating Set (CDS) is a set of nodes in the network such that all nodes in the network are either in the CDS or directly attached to a node in the CDS. A Minimum Connected Dominating Set (MCDS) is the smallest CDS, in terms of the number of nodes in the CDS, for the entire network. The size of the MCDS is the minimum number of retransmissions required in a broadcasting process so that all nodes in the network receive the broadcast message Beacon Messaging Each node periodically broadcasts a Hello beacon message in its neighbourhood. The Hello message contains information about location of the node, its velocity and direction of moving, the 1-hop neighbour list of the node, and the set of MPRs for the node. The Hello message is used by MPR and MCDS based broadcasting strategies. One or more broadcasting techniques have been proposed under each of the above four families. The objective of all these broadcasting techniques is to minimize the number of retransmitted messages and the number of nodes retransmitting the message. 4. ON DEMAND ROUTE DISCOVERY On-demand routing protocols [2-4] discover a route between source destination pair with help neighbours information and they never need of topological information about the entire network, and thus there is no periodic update of routing information but efficient route discovery approach is very important to improve the network performance. When a sender needs a route to some destination, it broadcasts a RREQ packet to its one hop neighbours. Every neighbouring node rebroadcasts the received RREQ packet only once if it has no valid route to the destination. Each intermediate node that forwards the RREQ packet creates a reverse route pointing towards the sender. When the desired destination node or an intermediate node with a valid route to the destination receives the RREQ packet, it replies by sending a route reply (RREP) packet. The RREP packet is unicast towards the sender along the reverse path set-up by the forwarded RREQ packet. In traditional AODV, an intermediate node rebroadcasts all RREQ packets that are received for the first time. Assuming no intermediate node has a valid route to the destination and is the total number of nodes in the network, the number of possible rebroadcast in AODV is 1. The basic probabilistic broadcast route discovery is simple. A source node sends an RREQ to its immediate neighbours with probability of broadcast =1.When an intermediate node first receives the RREQ packet, with probability < 1 it rebroadcasts the packet to its neighbours and with forwarding probability 1 it simply drop the packet. Since the decision of each node to rebroadcast a packet is independent, the possible number of rebroadcasts is x ( 1). 5. PROBABILISTIC BROADCAST ON DEMAND ROUTE DISCOVERY Prediction of density of node in the network is not always feasible because of mobility speed. Under such conditions, fixed probabilistic route discovery can suffer from a degree of inflexibility, since every node is assigned as fixed probability regardless of current status of the network. Forwarding probability should be high if a node located in a denser region compared with sparse region. Dynamic probabilistic route discovery approach is used to adjust the forwarding probability at a node based on local neighbourhood information gathered. If the number of neighbours is more than the average number of neighbours and such node is located at a dense region is considered. The neighbourhood information is obtained by hello protocol to construct a 1-hop neighbour list at every node. A node that receives a hello packet from its neighbour node N periodically, creates an entry for N first time, else it updates the entry for N. If there is no periodic hello for a particular node for with in time of threshold that node is no longer valid and removes the entry for N from its neighbour table. The hello interval and its size can drastically consume the network resource and degrade the overall performance of the network. But the frequency of hello packets would be beneficial factor for the accuracy neighbour information. A size of 4 bytes and 2 bytes of hello packets with identification number respectively at a interval of 1.5 seconds is selected. Finally the probability of broadcast at a node is set LOW when relatively large percentage of its 1-hop neighbours are covered by the broadcast and region is considered as dense. Also, the probability is set HIGH when small percentage of its neighbours is covered and region is considered as sparse and broadcast probability is adapts dynamically the at each node according to the number of neighbours. 6. SIMULATION SETUP The simulation is carried out with the Network Simulator (NS) 2.34 event driven open source software on a platform with and Ubuntu 9.10.The topological area of 1000 m 1000 m region is chosen with fixed node density as 50 deployed, random waypoint mobile model[15], network setup consists of 50 nodes are CBR data sources placed randomly and transmission range of 250 m moves at variable speed from 10 to 40m/s. The simulation is allowed to run for 100 seconds. The Distributed Coordination Function (DCF) of the IEEE protocol is used as the MAC layer protocol. Table. no 1 Simulation parameters Parameter Value Simulator Ns2 Routing protocols PB-AODV,AODV, evaluated DSDV Simulation time 100 s Number of nodes 50 nodes Simulation area 1000 m X 1000 m Transmission range 250 m Mobility Model Random-waypoint Traffic type CBR Data payload 512 bytes/packet Packet rate 4 packets/s Link bandwidth 2 Mbps 7. RESULTS AND DISCUSSION This section presents the impact of node mobility on the performance of PB-AODV, DSDV and AODV as the base routing protocol. The main aim is to reduce the routing overhead in the route discovery, therefore minimizing collision and increasing the overall performance in the network. The performance of three protocols is evaluated using the following important QoS metrics. They are control overhead,

4 packet delivery ratio, Average throughput, and Endto-end delay. 7.1 Routing Overhead It represents the ratio of the number of control packets generated by the protocol to the number of data packets received by the destinations. It considers routing overhead and the MAC control overhead (ARP packets and control packets such as- RTS, CTS and ACK). The three route discovery algorithms impose vastly different amounts of overheads when the node mobility is increase. Fig. 2 demonstrates that PB- AODV can significantly mitigate the routing overhead incur during the route discovery process. The routing overhead is gradually increasing with mobility speed due to expense of control packets and overhead is moderate initially in PB-AODV when compared with the conventional AODV and DSDV. Finally, the mobility speed at 40m/s PB-AODV demonstrates superior performance over the conventional AODV and DSDV by further reducing the overhead as shown in Fig. 2. The results reveal encouraging benefits in overall routing control overhead but also show that network operating conditions have a critical impact on the optimality of the forwarding probabilities against node mobility. AODV for increasing mobility speed. The effects of node mobility on the performance of the three protocols in terms of average throughput is gradually reduced. The throughputs achieved by all the protocols are nearly same when the mobility around 20 m/s. Fig. 4. Throughput vs. Node mobility 7.4 End to End Delay It represents the average delay experienced by each packet when travelling from to destination due to buffering during route discovery, queuing delay at the interface queue, retransmission delays at the MAC, propagation and transfer times. Fig. 5 measures the end-to-end delay of data packets that have been received at the destinations. When node mobility increases, more RREQ packets fail due to broken link to reach the destinations due to high probability of packet collisions and channel contention cause by excessive redundant retransmissions of route request packets. When mobility speed is 40 m/s all the three protocols demonstrates the effects of poor network connectivity on delivery latency. However, PB-AODV shows that it can achieve better delay under high mobility. Fig. 2. Routing Overhead vs. Node mobility 7.2 Packet delivery ratio It is the number of packets received by the destination to those generated by the CBR source (or) the ratio of the number of data packets received by destination nodes to those sent by the source nodes. The results of the simulation experiments show that increasing mobility speed of the nodes the delivery ratio reduces for all protocols. Reasons for this reduction are packet collisions and dropped packets. and PB-AODV achieved higher delivery ratios than AODV and DSDV for all maximum speed values as shown in Fig. 3. Fig. 3. Packet delivery ratio vs. Node mobility 7.3 Average throughput Average throughput is defined total number of data packets received (bytes) at destinations in one second. Fig. 4 shows average throughput with increasing node mobility. From the above results PB- AODV can significantly reduce the routing control overhead and increased PDR and average throughput also benefit when compared with the conventional Fig. 5. End to end delay vs. Node mobility 8. CONCLUSION The major focus of this paper has been the analysis of new probabilistic route discovery algorithms based on locally collected information for routing protocols in MANETs, such as AODV and DSDV, that can significantly reduce the routing overhead and packet collisions that associated with the traditional simple flooding based route discovery in AODV while minimizing improving end-to-end delay increasing PDR and average throughput. The conventional AODV routing protocol implementation in ns-2 has been modified to obtain neighbour information. Extensive simulation experiments have been conducted base on impact of a node mobility and this approach can generate less rebroadcasts while keeping the reachability high. The results have revealed PB-AODV exhibit superior performance advantage in terms of routing overhead, average throughput, Packet delivery ratio and end to end delay compared with conventional AODV and DSDV. It would be an interesting prospect to examine the effects of probabilistic broadcast method

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