Research And Improvement Of A Cluster-Based Routing Algorithm For Wireless Sensor Network

Wireless sensor network, as the core part of "the internet of things" at present, highly integrate sensor technology, communications technology, and computer technology. In recent years, it shows a good application prospects in military, environmental monitoring, health care, intelligent transportation and other areas. In wireless sensor network, the node energy is limited. To organize the cluster structure and use the node energy effectively, which is the important part for routing algorithm.In this paper, the existing clustering routing algorithms and the algorithms based on particle swarm optimization is described in detail, and its research status and weaknesses are analyzed. In the traditional clustering algorithm, the cluster head is selected randomly and the energy dissipation of the network is not even. Based on sensor network nodes within the cluster and the distribution of residual energy, we define the energy density for the cluster. In the cluster head selection, considering the residual energy of the cluster head nodes, information transmission loss, as well as the energy density for the cluster and other factors, the binary particle swarm optimization (BPSO) algorithm is applied to optimize the cluster head selection. Subsequently, the proposed algorithm is improved in the paper; Based on energy distribution, energy-weighted average distance is defined. The fitness function is redefined by using energy-weighted.At last, we simulate the proposed algorithms by Matlab simulator. Results from the simulation indicate that the propose algorithm effectively balances the energy consumption of nodes in the network, and a higher network lifetime is reached compared with LEACH and PSO-C.