Energy Efficient Clustering Protocol Using PEGASIS Routing Protocol and Feed Forward Neural Network For Wireless Sensor Network
Wireless sensor networks consist of Sensor nodes with small battery power with limited Energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. Several network layer protocols have been proposed to improve the effective lifetime of a network with a limited energy supply. In this thesis a centralized routing protocol called power-Efficient Gathering in Sensor Information systems (PEGASIS) clustering protocol with Feed Forward Neural Network(FFNN) is proposed which distributes the energydissipation evenly among all sensor nodes to improve network lifetime and average energyconsumption.Another problem occurs when the transmission path meets with some sort of failure like a path failure or node goes to sleep mode. The focus, however, has been given to the routing protocols which might change the path or follow the different route to reach to the specified destination .So in this thesis, the state-of-the-art routing technique is proposed using PEGASIS Protocol with Feed Forward Neural Network (FFNN) technique to choose an alternative path in WSNs and compare the evaluated normal PEGASIS result and enhanced PEGASIS with FFNN.Simulation results shows that the outcome in terms of parameters such as Throughput, Packet loss as well as Energy consumption is better in PEGASIS with FFNN.
Wireless Sensor Network, Enhance Routing Protocol (PEGASIS), Artificial Approach (FFNN).