Research On Invulnerability Optimization Of Wireless Sensor Networks Based On Natural Connectivity

Because the miniature sensor nodes in the Wireless Sensor Network(WSN)have the characteristics of limited energy and low hardware performance,the sensor nodes can easily fail to work due to their own energy exhaustion or external attacks.Once the sensor node fails,it may have a huge impact on the normal operation of the WSN,and even cause the network to collapse.Therefore,in order to maintain the stable and reliable operation of WSN,it is very necessary to optimize the survivability of WSN.This paper uses graph theory to abstractly describe the nodes and edges of WSN,after analyzing the characteristics of the WSN topology,the WSN survivability is quantified,and the WSN topology survivability optimization model is established.Finally,the heuristic algorithm is used to solve the model to achieve the goal of WSN survivability optimization.The main research contents are as follows:(1)This paper analyzes and summarizes the research status at home and abroad and finds that the current WSN survivability optimization mostly adopts the scheme of increasing the redundant nodes and links in the network.However,WSN often has a large number of nodes.After adding nodes and links,not only the node degree value will be changed,but also the data transmission delay and the increase of network cost may be caused.Aiming at this problem,after studying the topological structure characteristics of WSN,this paper chooses the optimization method of keeping the node degree value for edge reconnection to optimize the survivability of WSN.(2)This paper introduces natural connectivity as the invulnerability measure of WSN,natural connectivity is a new network survivability measure based on network characteristic spectrum.When calculating network survivability,natural connectivity has the advantages of efficient calculation and stable results.In order to prove the validity of natural connectivity as a measure of WSN invulnerability,this paper compares the computational complexity,stability and monotonicity of natural connectivity with other network invulnerability indicators,and use the CC2430 module to build a hardware experimental platform to analyze the changes in the natural connectivity and critical removal ratio after removing the nodes,and the host computer data packet reception of the corresponding network.(3)In the process of optimizing the degree of protection while reconnecting,the data transmission capacity of the network and its survivability are in conflict.While optimizing the survivability of the WSN,it is necessary to take into account the data transmission capacity of the network.Therefore,this paper optimizes the survivability and data transmission capabilities of WSN with dual objectives,in which natural connectivity and the average shortest path length from ordinary sensor nodes to sink nodes are used as the optimization goals for the survivability and data transmission capabilities of WSN,respectively.Through reasonable constraint assumptions,a WSN survivability optimization model based on natural connectivity is established.(4)In order to solve the dual-objective optimization model of this paper,Aiming at the slow convergence speed of the multi-objective simulated annealing algorithm,this paper improves the algorithm,uses the improved algorithm to solve the Pareto optimal solution set of the model,and outputs the network topology after survivability optimization.The simulation results and the characteristics of the topological structure are summarized and analyzed,and compared with the FASF model on the survivability and data transmission ability of the WSN after being attacked.The comparison results prove that the use of this model can effectively improve the survivability and data transmission capability of WSN.