Dynamic Spatial-Correlation-Aware Topology Control of Wireless Sensor Networks Using Game Theory

With the increasing applications of Internet of Things (IoT), service quality becomes more and more important. The topology control of wireless sensor networks (WSN) is one of the key techniques to optimize the quality of service (QoS) of IoT. Game theory is an efficient approach of WSN topology control through global optimization, which resolves the conflicting objectives of self-regard sensor nodes. However, many existing topology control algorithms using game theory waste energy due to the transmission of redundant sensed data. In this study, we present a novel dynamic spatial-correlation-aware topology control method (TC-GSC) using game theory to reduce the redundant data. In TC-GSC, the monitoring region is divided into several spatial-correlation areas, and only one active node is periodically selected for each area. Based on the collected information of active nodes, the sink node computes the transmitting power level using game theory and generates the connected topology. Moreover, the WSN topology can be dynamically updated when the active node's remaining energy becomes greatly uneven, or the active node's working time exceeds the threshold. Extensive simulation results demonstrate that TC-GSC can effectively improve the energy balance of nodes and significantly reduce the energy waste, thus prolonging the lifetime of networks.