Distributed Fuzzy Sets-based Clustering Algorithm for Heterogeneous Wireless Sensor Networks
Shao-Juan Xu, Haixia Yu, Liqiang Diao, Zhong-Gao Sun · 2015
Clustering provides an effective way for data gathering in wireless sensor networks.In this paper, a new distributed clustering algorithm called DFSC that maximizes lifetime for energy heterogeneous wireless sensor networks is proposed, in which the cluster head selection approach is based on the concept of fuzzy sets.In DFSC, a membership function, a fuzzy enhancement function, and a converting function are interwoven during the cluster head selection phase.As a result, a node with higher residual energy and lower communication cost to base station will have more chance to become a cluster head.So DFSC can better handle the heterogeneous energy capacities.Simulation results under various network scenarios show that this algorithm outperforms some existing clustering methods, in terms of both the network lifetime as well as the network data capacity.