Reliable multipath routing in mobile ad hoc networks using hybrid computational intelligence algorithms

Abstract

Due to mobility and frequent node failure, the topology of a mobile ad hoc network (MANET) is highly dynamic. Routing protocols should adapt to such dynamism, and continue to maintain connection between the source and the destination. A hybrid computational intelligence-based multipath routing algorithm is presented in this chapter. The proposed method employs Hopfield neural network (HNN) as a disjoint path set selection tool for choosing disjoint paths that maximise the network reliability. The parameters of Hopfield model are also optimised by particle swarm optimisation (PSO) algorithm. This method selects disjoint paths in such a way that the network reliability is maximised. For this purpose, each node in the network is equipped with an HNN. Simulation results show that the proposed PSO-optimised HNN-based routing algorithm has better performance as the reliability of multiple paths is increased while the number of algorithm iterations is reduced as compared with the non-optimised HNN multipath routing. In addition, the PSO-optimised HNN-based routing algorithm shows better performance in terms of reliability and number of paths when compared with the backup path set selection (BPS) algorithm.