LUNAR: Working and Performance Evaluation in MANETs

Background/Objectives: Load eqUilibrium Neighbor Aware Routing (LUNAR)1 is proposed to address broadcast storm problem. In this paper, we discuss algorithm, flow-chart, working example along with simulation results of LUNAR in detail. Methods/Statistical Analysis: To address the problem, existing reactive routing protocols use one of the node metrics such as size of routing table, available queue space, neighbor count, available battery life, etc. However, measurement of single parameter at an intermediate node may not be the true measure of route stability or lifetime. LUNAR combines the advantages of neighbor coverage knowledge and load balancing techniques to implement decision making system at every intermediate node. Findings: We evaluate the performance of LUNAR with respect to performance metrics like Normalized Routing Overhead, End-to-End Delay and Packet Loss Rate in different network scenarios. LUNAR minimizes the routing overhead of the network by 31-54% compared to AODV and NCPR due to the reduction in routing packets required for route discovery. LUNAR reduces end-to- end delay by 15-32% and packet loss rate by 9-35% compared to AODV and NCPR. Applications/Improvements: Simulation result shows the reduction in rebroadcasting of routing packets.