Adaptive Routing Protocol in Mobile Ad-Hoc Networks Using Genetic Algorithm

Abstract

Mobile Adhoc Network (MANET) is a wireless network in which data is transferred in a forwarding direction from the source node to the destination node via multiple intermediate nodes. Packets collision is considered one of the most crucial limitations in MANETs because the nodes in the network move in random directions at a random velocity which increases the probability of collision and this will harm the throughput, the routing overhead, and the end-to-end delay. Also, frequent node mobility leads to a topological change and link instability and this reduces the data delivery rate. Because of limited available paths to the destination node or having a high traffic load, the possibility of traffic congestion augments at the intermediate nodes which in turn affects the packet delivery, particularly with real-time applications in MANETs. In this paper, we propose an adaptive routing protocol based on a bio-inspired genetic algorithm (GA). We optimize the multiple paths returned by the AOMDV mechanism (AOMDV-FG) to select the best path to the destination. The route with the highest fitness value is considered the most optimum route. Lastly, we compare our proposed protocol with AOMDV-TA and EHO-AOMDV. We have used routing overhead, end-to-end delay, throughput, energy consumption, and packet delivery ratio as key metrics for the performance evaluation of our proposed model.