Multiobjective Optimization for Topology and Coverage Control in Wireless Sensor Networks

Coverage, connectivity, and network lifetime are important issues in wireless sensor networks (WSNs). Balancing the energy consumption in the network, reducing the transmission range of nodes, and density control of active nodes are approaches to extend the network lifetime. However, transmission range reduction and smaller number of active nodes can affect the network topology and may cause the network to be disconnected. So, there exist conflicts among lifetime, coverage, and connectivity. In this paper, these conflicting issues are considered and an evolutionary multiobjective optimization approach based on nondominated sorting genetic algorithm-II (NSGA-II) is proposed to optimize them. Simulation results demonstrate that the proposed algorithm can improve the network lifetime and coverage while maintaining the network connectivity.