A Hybrid Weight-Based Clustering Algorithm for Wireless Sensor Networks

Clustering in wireless sensor network (WSN) is an efficient way to structure and organize the network. The cluster head (CH) forms dominant set in the network responsible for the creation of clusters, maintenance of the topology and data aggregation. A cluster head manages the resource allocation to all the nodes belonging to its cluster. In this paper, we propose a novel distributed clustering approach called Hybrid Weight-based Clustering Algorithm (HWCA). HWCA considers the neighborhood, the distance from the base station combined with the consumed energy as a hybrid metric to elect cluster head. The time required to identify the cluster head does not depend on the number of node and can be computed in a finite number of iterations. Our solution also aims to provide better performance such as maximizing the life time, reducing the number of lost frames in order to satisfy application requirements. Simulation results show that HWCA improves the net- work lifetime and reduces the number of lost frames compared with other similar approaches.