Abstract:In order to solve the multi-factor conflict problem in cluster head election process, a clustering algorithm based on adaptive inertia weight chaotic particle swarm optimization (AWCPSO) is proposed to optimize the cluster head election and extend the network life cycle. This algorithm considers the residual energy of the nodes, the distance from the base station and the probability of the node as the cluster head during the cluster head election process. At the same time, it uses the adaptive inertia weight chaotic particle swarm algorithm to optimize the cluster head election, and elects the cluster members around the node communication range. The number of cluster heads can satisfy the optimal number of cluster heads, which further improves the energy efficiency of the network. The simulation results show that the proposed algorithm can save energy more effectively compared with the SEP and DEEC algorithm, and the stability and lifetime of the network can be improved by 62.31% and 16.45%, respectively.