Energy-Efficient Collaborative Communication for Optimization Cluster Heads Selection Based on Genetic Algorithms in Wireless Sensor Networks

Abstract

To solve the energy constraint problem caused by the neighborhood of the sink, which is burdened with heavy relay traffic via multihop communication and tends to die earlier, a new energy-efficient collaborative communication model is proposed based on genetic algorithms in wireless sensor networks (WSNs). By setting the threshold value for a new generation judgment function, the proposed algorithm would be capable of judging whether the sensor nodes can be a cluster head. Then, the genetic algorithms will filter out some nodes from these temporary cluster heads to get the final cluster heads. Simulation results show that the proposed algorithm can allocate energy to each node of WSNs and postpone the death of the first node. In this manner, the lifetime of WSNs is effectively prolonged.