TLGT: Two-Level Game Theory Model for an Energy-Efficient Cluster- Head Selection and Data Transmission in WSN

In an era of rapidly changing techniques, Wireless Sensor Network (WSN) significantly serves in technological development. A game theory model for cluster-head selection and data transmission is proposed focusing on enhancing energy efficiency in WSN via longevity in network lifetime. In the initial phase, sensor node clustering is accomplished using a recurrent game theory approach with a limited punishment mechanism. Then, following cluster formation, the cluster-head (CH) is selected using the Stackelberg game model, and the lemma for selecting CH that enables its utility function is proposed and proven. Based on Pareto’s principle, coalition game theory is used to reduce energy consumption, distance, and overloading when transmitting data. Subsequently, a Two-Level Game theory model for energy-efficient CH selection and data transmission is designed, where energy consumed by 500 nodes is just 2.1 mJ which is 50% better than the existing techniques. Thus, the proposed model performance appears to take advantage of a variety of parameters, including throughput, energy consumption, average residual energy, packet delivery ratio (PDR), and Packet Loss Ratio. The proposed model improves network stability by keeping the PDR at 100% until 200 nodes, causing the first node to die after approximately 6,000 rounds.