Adaptive Routing In Ad Hoc Wireless Networks Using Ant Colony Optimization

This paper presents a new adaptive and dynamic routing algorithm called AAODV for mobile ad hoc networks inspired by Ant Colony Optimization algorithms. This algorithm is proposed by maintaining the nature of the Ad hoc On-demand Distance Vector (AODV) routing through the use of Ant Colony Optimization. AAODV maintains the on-demand nature of AODV but works in an adaptive manner. It does not send any Route Request packet that AODV does. Rather it identifies its paths with the feedback of previously traveled packets and updates and maintains the paths accordingly. This routing technique is a probabilistic adaptive technique that can change its route with the change of network topology by learning the environment. We evaluate AAODV algorithm by comparing it to AODV. Our simulations show that the AAODV algorithm provides better performance in average delay, packet loss, bandwidth overhead, and throughput than the AODV algorithm.