GKFCR: An Improved Clustering Routing Algorithm for Wireless Sensor Networks
Hongbing Li, Jun Ou, Hao Cui, Shangfei Zhao, Die Zeng, Yuning Wang · 2022
For the problems of uneven clustering and the randomness and singularity of cluster head election in wireless sensor networks (WSN), the paper proposes a cluster routing algorithm of K-means based on genetic algorithm and fuzzy control (GKFCR). The algorithm optimizes K-means clustering center problem by genetic algorithm during the clustering. And then fuzzy control is used to the election of cluster heads by calculating the probability of the nodes selected as cluster heads. The simulation results show that, compared with LEACH, LEACH-C, K-means and TSILEACH algorithm, GKFCR algorithm could attain a better clustering effect. It can effectively delay the time point of producing the first dead node and balance the energy consumption of the whole network.