Bio Inspired and Evolutionary Approaches to Optimize MANET Routing

Mobile Ad Hoc Network (MANET) is a dynamic multihop wireless network which is established by a set of mobile nodes on a shared wireless channel. One of the major issues in MANET is routing due to the mobility of the nodes. Routing means the act of moving information across an internet work from a source to a destination. When it comes to MANET, the complexity increases due to various characteristics like dynamic topology, time varying QoS requirements, limited resources and energy. There are various bio inspired and evolutionary approaches including Genetic Algorithm (GA), Neural Network, Evolutionary programming (EP) exploited for routing optimization in MANETs. The Swarm Intelligence based algorithmic approaches; Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) are more promising in providing loop free, energy-aware, and multi-path routing in mobile ad hoc. In this paper we study some PSO and GA algorithms to optimize the MANET routing.