Research On Node Scheduling Algorithm Based On Data Similarity In Wireless Sensor Networks

Wireless sensor networks use nodes placed in the monitoring environment to monitor the target information required by users in different regions,and finally feedback the required data information to users.It is currently widely used in medical monitoring and battlefield reconnaissance.The nodes are usually powered by batteries,and their own power is limited.They are usually placed in dangerous and complex environments that are difficult to access by humans,and need to work for a long time.When the battery is used up,the node will die and go offline from the entire network.Therefore,the energy efficiency of the node itself has become an urgent problem in the design of wireless sensor networks.In order to solve the problem of imbalanced energy consumption of nodes in the network,this paper proposes a wireless sensor network node scheduling algorithm based on data similarity.This algorithm mainly consists of a distributed nonuniform clustering algorithm with balanced energy consumption and nodes based on data similarity.The sleep scheduling strategy consists of two parts.The main content of this article is as follows:Firstly,a distributed non-uniform clustering algorithm with balanced energy consumption is proposed.Aiming at the problem of imbalanced energy consumption of nodes in different geographical locations in the network,the algorithm sets the corresponding competition radius for nodes in different geographical locations.Nodes in different geographical locations need to be based on the distance from the node to the sink,their current energy level,and neighbor nodes.To set its own corresponding competition radius.Within the competition radius of each node,each node compares the cluster head election weights of itself and its neighboring nodes,and selects the node corresponding to the largest weight to become the final cluster head.Ordinary nodes are based on the received election weights of neighboring nodes.Join the cluster formed by the node with the largest weight.Secondly,based on the above clustering,a node sleep scheduling strategy based on data similarity is proposed.A fuzzy equivalence matrix is constructed based on thedata similarity between nodes calculated from the data collected by the active nodes in different data collection sub-period clusters.Clustering analysis is performed based on the dual clustering criteria of neighbor perception nodes and data similarity thresholds to obtain a redundant node set.Under the condition of avoiding the perception of blind spots,according to the different clustering conditions of redundant nodes,the relative positions between nodes and the remaining energy are comprehensively selected to further select the sleeping nodes,and the sleeping nodes set obtained in different sub-cycles are merged to obtain the final sleeping node.Do sleep scheduling.This sleep strategy effectively reduces the collection of redundant data and reduces the energy consumption of nodes.Finally,OMNeT++ software was used to test the proposed algorithm.By comparing and analyzing with other sleep scheduling algorithms in terms of network energy efficiency,network load balancing and data accuracy.According to simulation results,the proposed algorithm has excellent performance in reducing energy consumption of nodes and improving network survival time.