Adaptive TAKAGI-SUGENO fuzzy model using weighted fuzzy expected value in wireless sensor network

Limited energy resources of sensor nodes are the main constraint in wireless sensor networks, many researches applied multi input single output fuzzy models for cluster heads election. These models are less interpretable and built from expert´s knowledge. The adaptive TS fuzzy model sensor node (ATSFMSN) protocol aims to adapt MIMO TAKAGI-SUGENO model for cluster heads and relay nodes election. Adaptive TAKAGI-SUGENO model is done by fuzzy cluster algorithms based on fuzzy expected value. In addition to, fuzzy rule base is reduced by similarity measure and fuzzy cluster algorithm. Similarity measure requires two parameters to estimate overlap degree. The simulation results show the ATSFMSN protocol is more energy efficient routing protocol against LEACH, CHEF, and FCM routing protocol.