ACO better as Optimization Technique in MANET: A survey

Mobile Ad Hoc Networks are networks that consists of wireless nodes, randomly organized and placed without any support of fixed communication infrastructure. Mobile means Moving Nodes in network, Ad hoc represents “For this purpose� (i.e. Latin) & Ad hoc network – sums to be self-organizing, self-configuring and adaptive network. Hereby, all nodes can be understood to be mobile, can enter or leave communication network at any moment of time. One of major issues out of many is routing. There are various type of optimization schemes that play vital role in minimizing the efforts of routing for any network. This includes Evolutionary Algorithms, Genetic Algorithm (GA) i.e. stochastic method of searching which impersonates the natural evolution and societal behaviour of species. Learning automaton (LA) is an adaptive decision-making element situated in a random atmosphere that learns the best action through repeated communications with its environment. The actions are chosen according to a specific likelihood distribution which is updated based on the environment response the automaton obtains by execution of a specific action. Another conventional method many researchers have proposed adoption of Swarm Intelligence for routing. This refers to complex behaviour from simple individual behaviour and interaction which are more often witnessed in nature amid Ants, Bees, Fishes or Birds, etc. Ant Colony optimization has been proved to be better technique for developing routing algorithm for MANET.