ENERGY AWARE ALGORITHM FOR IMPROVED AODV ROUTING PROTOCOL

Abstract

A Mobile adhoc network is a collection of wireless mobile nodes which can provide scalability and independence for mobile topologies. These wireless mobile nodes are battery powered hence the need for energy conservation in order to allow an increase in network lifetime. Energy conservation is very important in applications such as Military operations and Emergency Rescue operations where network infrastructure is not readily available. Other application areas where the Wireless Sensor networks have gained a considerable recognition include security and surveillance, vehicular movement, weather monitoring, industry applications etc. Sensor nodes can sense the environment in which they are deployed and together in a cooperative fashion can propagate sensed data either directly or through one another in a well-coordinated strategy (routing) to the desired destination. In this thesis we developed an energy aware algorithm which uses K-means algorithm as the Clusterhead head selection method that is aimed at improving the network performance of AODV (adhoc on-demand distance vector) routing protocol. The improved energy idea uses the concept of drain count in sensor nodes which works as follows: Each node is set with an initial energy value which basically determines how long it’s going to last in a network and to make sure our network has the highest lifetime possible we set up a threshold energy value. If a particular path has a single node with its energy lesser than that of the set threshold, then the drain count of that particular path is incremented by a factor of one (1). The drain count will serve as the parameter on which we can choose the path that is most likely to prolong the network lifetime. The path with the least drain count obviously will be the one that is chosen because it has few nodes with energy below the energy threshold. We then introduce K-means in the energy efficient system for the formation of clusters in our system and again this will help in shortening the transmission path. Performance evaluations are done with respect to network lifetime, throughput, end-to-end delay, packet delivery ratio using Ns2 simulator.