On the Effects of Using Proactive Components on the Performance of Ant-based Routing Algorithms in MANETs

A number of routing algorithms based on Ant Colony Optimization have been proposed for wireless networks. However, there has been little attention paid to understanding the role of proactive components used in the structure of some Ant-based routing algorithms and the way they influence the performance of these algorithms. In this paper, a comprehensive study is launched to answer how the proactive agents influence the performance of AntHocNet, a hybrid multipath routing algorithm in MANETs. To evaluate the general effects of these components two versions of AntHocNet are implemented. The first one is a version where proactive learning is switched off and the second one is based on the original version of this algorithm. The sensitivity of two standard measures of effectiveness in MANETs, being delivery ratio and average end to-end delay are reported for both versions. Simulation results indicate that AntHocNet including proactive agents gives much better outputs than the one including no proactive components.