CFGA: Clustering Wireless Sensor Network Using Fuzzy Logic and Genetic Algorithm

Wireless sensor networks have numerous nodes with limited energy which have the ability to monitor around themselves and these nodes are scattered in a limited geographic area. One of the important issues in these networks is increasing the network lifetime. In this study, we introduce an efficient protocol for trade-off between loads and increase in life expectancy of the network, known as CFGA (Clustered wsn using fuzzy logic and genetic algorithm) which uses the single - step method for intracluster communication and multi - step for intercluster communication. At the beginning of each round, each node first checks its fuzzy module, and based on output of the fuzzy module, if the clusterhead capability exists for node, it would be ready ( in each region, number of the best nodes would be ready), then at the base station by using genetic algorithm and the location of clusterheads based on minimum energy consumed, the optimum network nodes are determined. In this study, consumption of energy for nodes which are not capable of becoming clustered is prevented and also only nodes with high capabilities in genetic algorithm take part in order to converge faster to the optimum solution.