Optimizing and Enhancing the Lifetime of a Wireless Sensor Network Using Biogeography Based Optimization

Wireless sensor networks (WSNs) contain tiny sensor nodes which are operated battery and have a limited lifetime. Improving the network lifetime of a WSN by optimal battery usage is an area investigated by many researchers in the past. In this work we propose a new nature-inspired technique Biography based optimization for energy efficient clustering (BBO-C) in a WSN. BBO-C takes into account novel parameters like minimization of Cluster Head (CH) energy dissipation and the transmission distance between both sensor nodes to CH and sink to CH which results in better distribution of sensors and a well-balanced clustering system, thus enhancing the network lifetime of a WSN. BBO-C is simulated using Matlab and provide very good results in terms of network lifetime, packets sent to the base station and load distribution. BBO-C outperforms past works like PSO based clustering, GLBCA, GA and LDC by 38.2%, 53.6%, 58.8% and 62.2% respectively