Research On Topology Control Of Wireless Sensor Networks Based On Non-cooperative Game

With the rapid development of information technology,various intelligent sensing devices and artificial intelligence applications are gradually spread to all corners of society,and people's lives are inseparable from intelligent sensing technology.As the underlying support technology for communication between IOT devices,wireless sensor networks has been paid more attention and widely used,so the research of sensor technology and wireless network communication technology is of great significance.Wireless Sensor Network(WSN)is a Wireless Network formed by a large number of cheap and low-power sensor nodes connected by a self-organized way.It is usually deployed in regions inaccessible to human beings such as harsh environment and dangerous terrain to perceive and collect information of various monitoring objects.On the contrast with traditional wireless networks,sensor nodes are mostly powered by batteries with a small capacity and batteries are not easy to replace.Therefore,under the premise of limited node energy,how to reduce the node's energy consumption and improve the energy utilization efficiency to delay the network's life cycle has become a key issue that wireless sensor networks need to solve urgently in practical applications,which is also a hot topic in this field.Aiming at the problem of limited energy when nodes work together in wireless sensor networks,after in-depth research and analysis,from the perspective of topology control,the rationality and feasibility of applying non-cooperative game theory to build energy-saving models are explained from different perspectives.The specific research content is as follows:For the planar network topology,this paper proposes a node power control algorithm based on potential game.This algorithm abstracts the power control problem of each node in the network into a potential game model in non-cooperative game theory,and effectively coordinates the working mechanism between nodes by designing a reasonable benefit function.In the design of the benefit function,the algorithm comprehensively considers the transmit power of the nodes,the communication interference between the nodes,the current remaining energy of the nodes,and the network connectivity.The nodes adjust the current power through the optimal response strategy,and finally The Nash equilibrium point that makes the wireless sensor network converge to the optimal transmit power.The simulation results show that the node power control algorithm based on the potential game can effectively reduce the transmit power of the nodes,balance the load between nodes,improve the energy efficiency of the network,and extend the life cycle of the network on the premise of ensuring network connectivity and robustness.For hierarchical network topology,this paper proposes an energy-balanced clustering algorithm based on mixed strategy games.The algorithm uses a periodic cluster-head rotation mechanism.In the cluster-head election stage,the current residual energy of the nodes and the average distance to neighboring nodes are fully considered to define the gain and loss when any node is declared as the cluster head.Finally,all nodes decide whether to declare as cluster heads according to their calculated equilibrium probability.So that nodes with more remaining energy and less loss have a higher probability of becoming the cluster head,thereby ensuring that the election strategy of the cluster head is more reasonable.Meanwhile,in order to avoid the situation where multiple neighboring nodes are selected as the cluster head at the same time during the cluster head election process,a two-round cluster head election mechanism is introduced,and the true cluster head is selected from the set of potential cluster heads through an iterative algorithm.Simulation results show that the algorithm can optimize the network cluster structure and balance the load of network nodes,thereby balancing the energy consumption of the overall network,effectively improving the problem of premature energy holes in the network,and extending the network's survival time.