Genetic algorithm based cluster head optimization using topology control for hazardous environment using WSN

Wireless Sensor Network (WSN) is widely used in recent years for the applications where human intervention is impossible. In case of nuclear power plant if any small delay occurs for data forwarding due to any node failure may results in severe disaster. Hence effective Topology Control is required to obtain an energy efficient sensor network even if any node fails. An efficient topology control using genetic algorithm based cluster head selection is presented in this paper. In this work, three tier sensor network architecture is developed and is comprised of Super Head nodes, Cluster Head nodes and Cluster Slave nodes. The results obtained for the developed three tier architecture is compared with two tier and one tier architectures. Residual Energy, Bandwidth and Memory Capacity are used as selection criteria. Quantitative analysis is also carried out to study the impact of N-tiers on the performance of the proposed algorithms. From the quantitative analysis of the proposed methodologies on the N-tier architecture with various node densities, it has been proved that two tier architecture provides reduced energy consumption compared to others.