Clustering Algorithm Based on Fuzzy Comprehensive Evaluation for Wireless Sensor Networks

Energy efficiency and quality of service (QoS) are both required performances in the practical applications of wireless sensor networks. Clustering is one of main methods to achieve performance tradeoffs. In the clustering algorithm, the selection of the cluster heads is based on some criteria, which provides the opportunity to implement the performance tradeoffs. In this paper, a clustering algorithm based on fuzzy comprehensive evaluation method (CAFCE), is proposed to achieve both energy efficiency and QoS performance. Residual energy, location, number of neighbors, queue length and channel quality are taken into account as the factors that can influence the selection of cluster heads. Fuzzy comprehensive evaluation method is adopted to select appropriate cluster heads in order to achieve energy efficiency and QoS performance simultaneously. Each node obtains its own evaluation value. Then this value is mapped onto the time axis, and a time-trigger mechanism enables the node broadcast cluster head advertisement in the corresponding time slice. The rule of minimum transmission power is adopted to form the cluster. Simulation results denote that CAFCE algorithm has longer lifetime and better QoS performance than other algorithms.