A Distributed Fuzzy-based Clustering Scheme to Optimize Energy Consumption and Data Transmission in Wireless Sensor Networks

Due to importance of energy conservation in wireless sensor networks, clustering algorithms and then cluster-based routing schemes are widely designed and utilized in this kind of network. To collect data in the base station, each sensor node sends the sensed data toward the cluster head via single or multi hops. Multi-hop data transmission in the clusters yields unbalanced load of the cluster members. The nodes around the cluster heads have to forward all the received packets from the cluster area; thus, the rate of energy consumption of cluster members is unbalanced. Accordingly, the lifetime of network is shortened by dying the high load nodes. In this paper, a distributed fuzzy-based clustering scheme is proposed to optimize energy consumption and data transmission of wireless sensor networks. In the proposed scheme, the remaining energy and degree of the nodes, transfer time of packets, the hops to the base station, average distance to neighboring nodes and residual energy of the neighboring nodes are considered as the criteria for cluster head selection. Each node calculates its probability of becoming cluster head via a distributed fuzzy inference system. The evaluations show DEEFCA compared to EEDCF, DFLC and EADEEG schemes, enhances network lifetime respectively by 12.8%, 21.5% and 25.8%, also, the amount of data transferred by the network is increased by 19.7%, 71% and 167%.