Clustering techniques in wireless sensor networks have been widely utilized for their good performance in reducing energy dissipation and prolonging network lifetime. Once the cluster heads have been decided, the allocation of member nodes in the cross coverages formed by two or more clusters is critical to keep an energy balance on the cluster heads. In earlier studies, however, the allocation of member nodes simply depends on the distance or degree (the node number within the cluster heads’ communication radius) and, therefore, could cause imbalance to the cluster heads’ load and further degrade the whole wireless sensor network. To maintain the load balance of the cluster heads, in this article, game theory is introduced into the allocation problem of the member nodes. Before using the game theory approach, the number and distribution of cluster heads are first checked. If the cover rate of the cluster heads is low, then the node(s) uncovered by any cluster are randomly selected as new cluster head(s) to attain the cover rate required in the article. Furthermore, the number of cluster heads in a monitoring region is restricted. Finally, a game-based, energy-balance method is proposed and applied in the cluster-based routing protocols to improve their performance. For verification, the proposed method is embedded into the localized game theoretical clustering algorithm and hybrid, game theory–based and distributed clustering algorithm, which are two game theory and typical cluster-based routing protocols. The experimental results show that both of the improved protocols do balance the loads of the cluster heads and achieve better performance than their original versions in spanning the lifetime and balancing the energy in wireless sensor networks.
GTRF: A Game Theory Approach for Regulating Node Behavior in Real-Time Wireless Sensor Networks