An Improved Three-Layer Low-Energy Adaptive Clustering Hierarchy for Wireless Sensor Networks

Topology control in wireless sensor networks (WSNs) balances the communication load on sensor devices and increases the network lifetime and scalability. Hierarchical or cluster-based design is one of the approaches to conserve the energy of the sensor networks in which the nodes with the higher residual energy could be used to gather data and route the information. However, most of the previous work on clustering has adopted a two-layer hierarchy, and only few methods studied a three-layer scheme instead. Based on a three-layer hierarchy, this paper has proposed a semi-distributed clustering approach by considering a hybrid of centralized gridding for the upper level head selection and distributed clustering for the lower level head selection. The simulation results show that the proposed approach is more efficient than other distributed algorithms. Therefore, the technique presented in this paper could be further applied to large-scale WSNs.