WSN Clustering Based On Game Theory Research On Routing Algorithms

In the context of the AI era,the future world is an intelligent world where everything is connected,and all aspects of human life require intelligent sensor devices to collect and process information from the surrounding environment.As one of the fundamental technologies in the field of AI-aware communication,the research and development of Wireless Sensor Network(WSN)is of great significance.In WSN clustering routing algorithm,the design of reasonable clustering mechanism and cluster head selection mechanism can improve the energy utilization efficiency of network nodes.In order to reduce the network energy consumption and extend the network life cycle,this thesis proposes two game-theoretic-based clustering routing algorithms(Game-oriented Clustering Routing Algorithm-2D,GCRA-2D)and(Game-oriented Clustering Routing Algorithm-3D,GCRA-3D),in GCRA-2D routing algorithm,the optimal number of cluster heads is calculated based on the network model and node energy consumption model to reasonably partition the network,and one cluster head is selected for each partition to make the cluster heads in the network more uniformly distributed.In this thesis,a cluster head game model is constructed to determine the cluster head declaration probability of nodes in each partition,and each partition avoids the nodes with less energy to be elected as cluster heads through a hybrid strategy and equalizes the energy consumption of the network through a probabilistic zeroing mechanism.In GCRA-3D routing algorithm,we construct a 3D spherical network,calculate the optimal number of cluster heads of the spherical network model based on the mathematical characteristics of the spherical network and the energy consumption model,partition the spherical network based on the optimal number of cluster heads,select the optimal cluster heads in the partition using the cluster head game model to improve the energy utilization of the network,and reduce the amount of data transmitted by the cluster head nodes through the data fusion technique to save The energy of the cluster head node is reduced by data fusion.Through experimental simulation and comparison analysis,the GCRA-2D algorithm and GCRA-3D algorithm proposed in this thesis have certain performance improvement in reducing network energy consumption and extending network life cycle.