GTFR: A Game Theory-Based Fuzzy Routing Protocol for WSNs

Clustering is an approach exploited in wireless sensor networks (WSNs) to enhance their performance and energy efficiency. Therefore, cluster formation and proper cluster head (CH) selection are of utmost importance in such scenarios. The proposed method, game theory-based fuzzy routing (GTFR) protocol, optimizes both of these phases of network operation in WSN. In the proposed work, fuzzy clustering is utilized for forming clusters with the desired quality of having low intracluster communication distance (IACD). In addition, CH selection is based on game theory and a fitness function that ensures optimal CH selection during two sub-phases of CH selection [tentative CH (TCH) selection and final CH selection]. In conjunction with using a penalty function for the clustering game (CLG), the proposed work also considers the nodes’ history of acting as a CH as a fitness criterion to enhance performance by impartially rotating the role among all the nodes. The proposed protocol outperforms low-energy adaptive clustering hierarchy (LEACH), hierarchical structured cluster routing LEACH (HSCR LEACH), fuzzy C-means (FCM), and cluster tree-based routing protocol (CT-RPL) in terms of stability by 238.27%, 183.94%, 432.04%, and 47.31%, respectively. Rigorous simulations prove that the proposed protocol outperforms LEACH, HSCR LEACH, FCM, and CT-RPL in all three considered network scenarios.