Improved Differential Evolution in WSN Node Deployment

Computer Science and Engineering

WSN consists of a large number of tiny sensor nodes distributed over a large area with one or more powerful sinks or base stations collecting information from these sensor nodes. The sensor nodes are equipped with battery and whose battery cannot be replaced after deployment. Therefore, deployment of sensor nodes has serious impact on network lifetime. Deployment can be random or pre-determined. Random deployment of sensor nodes most of the times generates an initial communication gap in the sensing field even in a highly dense network. In either case, the resulting inter-node distances may cause lack of communication and subsequently degrades the network performance. In this paper, we have proposed an enhanced deployment algorithm based on Differential Evolution (DE). The main motive of our algorithm is to reduce energy conservation during deployment & communication between distance nodes and for this purpose; we are using differential evolution optimization method. The algorithm aims at extending network lifetime by using a minimum number of relays. We have measured results on homogeneous and heterogeneous models and the simulation results are showing that heterogeneous models are providing better results as compared to homogeneous models under differential evolution.

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