A Comprehensive Survey of Fuzzy Inference Systems Used for Clustering Problems in WSNs

Abstract

Intelligent computing has become the new standard for various industries and is considered one of the critical research trends today. With unique advantages under uncertain and varied conditions, clustering and routing in wireless sensor networks (WSN) using fuzzy-based intelligent computing have achieved considerable success. several surveys have been undertaken to analyze the effectiveness and application direction of fuzzy for tackling challenges in WSN. However, a systematic review of the application parameters for the input of the FIS system and its classification protocols on it has never been devised. Hence, this paper exploited the clustering problem based on the fuzzy inference system from the application methods to the input parameters related to the outcome. The recommendations in this paper may offer valuable solutions for researchers or implementers of practical systems.