A novel clustering algorithm based on particle swarm optimization for wireless sensor networks
Jing Zhao, Le Tian, Zhao Shuaibing · 2014
In wireless sensor networks, the energy supply is limited and the node will be dead while the energy is out of use. In order to solve the energy consumption problem about the sizes of clusters, a novel grid clustering algorithm based on location information is proposed in the paper: the node is planned to the corresponding grid according to the location information.While we can get the sizes of clusters adjusted based on different distance from the base station with particle swarm optimization algorithm to ensure that accurate cluster information away from the base station can be transmitted to the base station. From the simulation we can get the conclusions that the energy consumption is reduced and the network's lifetime is prolonged effectively, while the performance of the network's coverage and connectivity is not reduced.