A Heuristic-based Approach for Improvement the Performance of Probabilistic AODV Routing Algorithms in MANETS

Abstract

Mobile Ad hoc NETworks (MANET) are infrastruc-tureless networks that are mostly used in emergency situations where the base station is damaged. The most important applica-tion of such networks is in the military and more especially for search and rescue (SAR) applications. Therefore, it is important to investigate the effective parameters on the performance of such networks. In this paper, we focus on the probabilistic Ad hoc on-demand Distance Vector (AODV) routing algorithm which is a common routing algorithm in MANETs. Because of the importance of improving network performance and preventing collision, therefore in this paper, we propose an intelligent probabilistic method to improve the network’s performance by increasing the throughput and decreasing the average end to end delay. The proposed method is evaluated for probabilistic AODV by defining a probability density function (PDF) depending on factors such as network density, probability of forwarding the messages, and mobility using a cuckoo optimization evolutionary algorithm to find out the best probability of forwarding in order to maximize a cost function depending on throughput and average end-toend delay. The simulation results are provided using NS2 simulator.