Description

This work proposes Artificial Neural Network (ANN) based Ad-hoc On-demand Distance Vector (AODV) protocol for MANETs. A mobile ad hoc network (MANET) is a continuously self-configuring, infrastructure-less network of mobile devices connected without wires. Artificial neural networks are generally presented as systems of interconnected “neurons” which can compute values from inputs, and are capable of machine learning as well as pattern recognition thanks to their adaptive nature. Each device in a MANET is free to move independently in any direction, and will therefore change its links to other devices frequently. MANETs are a kind of Wireless ad hoc network that usually has a routable networking environment on top of a Link Layer ad hoc network. MANETs consist of a peer-to-peer; self-forming, self-healing network in contrast to a mesh network has a central controller. Each must forward traffic unrelated to its own use, and therefore be a router. The primary challenge in building a MANET is equipping each device to continuously maintain the information required to properly route traffic. Information update in some fixed time interval may produce traffic in the wireless network so to make adaptive time interval of these messages is a technique to improve the performance of the network. Hence in this paper, ANN based AODV reactive routing protocol is proposed to specify the frequency of Hello messages of AODV reactive routing protocol to develop the performance of Mobile Ad-hoc Networks. The whole model is performed in VHDL and Matlab integrated. By implementing like this, the process developed will be easier to understand and also this gives solution for visualization of results.