Research On Clustering Algorithm In Wireless Sensor Network

In recent years,the Internet of Things(Io T)technology has developed rapidly,and it has also driven the development of other industries.Wireless Sensor Networks(WSN)as the underlying technical support of Io T,has become a hot research field due to its low cost,easy deployment,and wide range of application scenarios.However,the node energy of WSN is limited and cannot supplement energy to the battery,resulting in a limited life cycle of WSN.Therefore,how to increase the use time of nodes and extend the service life of the network has become a technical problem in the WSN field.In the traditional clustering algorithm,the random selection of cluster head nodes will cause uneven distribution of cluster head nodes,resulting in uneven node load,excessive energy consumption of some nodes,and "energy holes",which will lead to the life cycle of WSN too short.In view of the above problems,this paper proposes three different clustering algorithms for selecting cluster head nodes.A clustering algorithm based on improved harmony search is proposed.The algorithm first improve the harmony search algorithm,then analyze the optimal number of cluster heads in the network,and consider the remaining energy of the node,the distance between the node and the base station and the number of neighbor nodes around the node,design the fitness function,and finally use the improved algorithm select the cluster head node.A clustering algorithm based on improved particle swarms is proposed.The algorithm first improves the particle swarm algorithm,and then introduces the dormancy mechanism of the neighboring node group,so that some nodes do not participate in the work when the network is running,and then reanalyzes the optimal number of cluster heads in the network when joining the neighboring node group,using The fitness function judges whether the cluster head node is selected properly,and finally the cluster head node is selected.A clustering algorithm based on fuzzy logic is proposed.The algorithm uses a fuzzy logic system to select cluster heads,and adds a sleep mechanism for neighboring node groups,comprehensively considering factors such as energy factor,distance factor,and the number of neighbor nodes,and obtains the probability of a node becoming a cluster head through fuzzy inference,which is used to select cluster heads node.Through analysis and simulation,the three algorithms proposed in this paper can effectively improve the energy efficiency of the network and extend the life cycle of the network.