Networks energy-efficient clustering algorithm based on fuzzy inference system
Ying Zhang, Rundong Zhou · 2017
Clustering routing algorithms have been widely used in Wireless Sensor Networks (WSNs) recently. However, relaying node with closer distance to cluster head will involve in higher data traffic and consume energy more quickly than the farther nodes, which may result in bad influence on load balancing in network system. Therefore, we proposed a fuzzy Logic based distributed energy-efficient clustering algorithm (FLDEEC). During cluster head (CH) election, we take nodes' energy, nodes' degree and neighbor nodes' residual energy into consideration as input parameters. Through fuzzy inference system, node uses its own information and its neighbor nodes' information to make a judgment to decide whether it fits to be a CH or not in a distributed way. FLDEEC algorithm can solve hot spot problem caused by communication in cluster, improve the efficiency of data transmission and extend the lifetime of the whole network by screening out nodes with bad conditions. The experimental results indicated that the FLDEEC algorithm is better than CHEF algorithm and DEEC algorithm in the aspects of data transmission, energy consumption and the number of living nodes.