A Lifetime-Enhanced Genetic Clustering Method for Heterogeneous Wireless Sensor Networks

To solve the problems of short lifetime and unbalanced load among clusters, the improved clustering method is proposed based on genetic algorithm (GA) for wireless static sensor networks with heterogeneous energy. In the process of mapping encoded chromosome into execution strategy, the sensor nodes whose member set is empty will be converted into membership, which is conducive to collect sensory information. Considering the constraints of single-round energy consumption, communication scheduling delay, residual energy and other factors, a novel fitness function is constructed to evaluate clustering strategy performance. Simulation results demonstrate that, the proposed method significantly outperforms existing methods in terms of network lifetime, energy consumption and the number of transmitted sensory packets.