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A mobile ad hoc network (MANET) is an autonomous network that consists of mobile nodes that communicate with each other over wireless links. An advent of new technologies and the demand for flexibility and ease in working environment, the use of Mobile Ad hoc computing is growing fast. Besides their use, Mobile Ad hoc networks (MANET) are assumed to grow in size too. They function in independent groups, containing some tens of nodes up to several hundreds of nodes. As the network size increases, it becomes common for the nodes to be dispersed in a larger area than the radio range of individual nodes. Under such conditions, we have to employ routing techniques such that the out of range nodes may communicate with each other via intermediate nodes. This problem of routing in mobile ad hoc networks is our focus of discussion in this paper, and a protocol is proposed as a solution. However, as the greedy algorithm used in Optimized Link State Routing (OLSR) protocol will choose the nodes with stronger coverability that creates the overlap of nodes in the MultiPoint Relay (MPR) selection, which will reduce the performance of the network. Multipoint Relaying is a technique to reduce the number of redundant retransmissions while diffusing a broadcast message in the network. Optimized Multicast Routing (OMR) protocol is able to change behavior in different situations in order to improve the metric like delivery ratio of the packet and throughput. The protocol is augmented by an optimization scheme, adapted from OLSR Protocol in which only selected neighbor nodes propagate the control packets to reduce the amount of control overhead in the network. The MultiPoint Relay (MPR) based mechanism of OLSR is used to perform an Optimized Forwarding Mechanism to efficiently do the flooding of broadcast messages in the Mobile Ad hoc Network. So, the number of MPRs is a key for the performance of the OLSR. An algorithm called “Necessity First Algorithm (NFA)” is used to- - select the optimal MultiPoint Relays in OMR protocol with the goal of solving performance problem of greedy algorithm.
Date of Conference: 27-29 Dec. 2010