Modeling MANET Utilizing Artificial Intelligent

In wireless communication, ad hoc mobile network is a collection of mobile nodes that are dynamically and arbitrarily located in such a manner that the interconnections between nodes are capable of changing on a continual basis. In order to facilitate communication within the network, a routing protocol is used to discover routes between nodes. Routing is a fundamental issue for mobile ad hoc network (MANET). Many routing protocols have been proposed for MANET and some of them have been widely used. This paper utilizes Artificial Intelligent (Neural network and neuro-fuzzy) to model MANET routing for three different routing protocols: dynamic source routing (DSR), ad hoc on-demand distance vector (AODV) and optimized link state routing (OLSR) and compare them with the traditional mathematical equation models. The results show that artificial intelligent (AI) models are more accurate and presenting to MANET than traditional mathematical equations.