Determination of cluster head via fuzzy inference system using weighted averaging based on levels and related application

Fuzzy logic is a dispensable element for computer technologies and artificial intelligence studies of present-day. Fuzzy logic has overcome to expand the world of machines by linguistic variables which only understand 0 and 1. As a result, fuzzy logic has been used in many areas in order to find solutions. Wireless sensor networks are one of the fields in which fuzzy logic can be used. Various methods have been developed for clustering sensors. Common purpose of these methods is gaining maximum profit by prolonging the lifetime of networks. In this study, how Fuzzy Inference System using Weighted Averaging Based on Levels (WABL) is used in clustering of sensors is explained. A new theorem has been proved in order to calculate the WABL value in composite fuzzy numbers resulting from the Fuzzy Inference System In the example presented, linguistic variables are used to determine the probabilities of sensors to be the cluster head and the clusters within the framework of these possibilities are constructed. It is seen how the clusters change in each cycle. In accordance with this change, new cluster heads are determined when necessary. This has allowed the network to increase its life and maximum utilization of the sensors.