Modelling and optimising a new hybrid ad-hoc network cooperation strategy performance using genetic algorithm

Abstract

The lifetime of an ad-hoc network depends on a mobile device?s limited battery capacity. In ad-hoc multi-hop communication, source nodes use intermediate nodes as a relay to communicate with remote destinations. As cooperation between nodes is restrained by their battery resources, it might not be in their best interests to always accept relay requests. Therefore, if all nodes decide how much energy to spend for relaying, selfish or non-cooperative nodes reduce cooperation by rejecting to forward packets to others, thereby leading to a dramatic drop in the network?s throughput. Three strategies have been founded to solve this problem: tit-for-tat, live-and-let-live, and selective drop. This research explored a new strategy in ad-hoc cooperation which resulted from the combination of the live-and-let-live and selective drop strategies. This new strategy is based on the suggestion to select fewer hops with a low drop percentage and sufficient power to stay alive after forwarding the data packets towards the destination or other relays at the route path. We used a genetic algorithm (GA) to optimise the cooperative problem. Moreover, the fitness equation of the GA population was designed according to the mixing of the two strategies, which resulted in a new optimized hybrid dynamic-static cooperation.