The Research On The Problem Of Dynamic Coverage Optimization In Wireless Sensor Networks

Wireless sensor networks are built on the development of the micro electro mechanical system, system-on-chip, wireless communication and low power embedded technology. Wireless sensors are widely applied to the field of military, aviation, disaster relief, and environment because of the low power consumption, low cost, distribution and self-organization.Network coverage, which is about the deployment of sensor network nodes to achieve the maximization of network coverage, was one of the fundamental problems in wireless sensor networks when we construct them. Considering the particularity of the coverage area and the poor degree of the covering environment, the nodes are deployed through the form of self-organization in the mode of dynamic coverage when deploying the nodes. The appropriate coverage control algorithm is used to adjust the sensor deployment according to the coverage performance of the monitoring region, so as to complete network coverage.Firstly, the basic principles of coverage control algorithm based on particle swarm optimization and differential evolution in the wireless sensor networks are introduced, and then the application effect of two control algorithms are compared. The control algorithm based on particle swarm optimization converges faster, but easily falls into premature. Otherwise, the control algorithm based on differential evolution converges relatively slowly, but its ultimate coverage is higher.Considering the advantages and disadvantages of the two algorithms, the control algorithm based on bat algorithm is proposed. The basic principles and the implementation process of the algorithm are elaborated, and the application effect of this algorithm is compared with the two algorithms above.The control algorithm based on bat algorithm effectively improves the coverage rate of the network, and its convergence speed is faster than that of the algorithm based on DE, but is slower than that of the algorithm based on PSO.In order to further improve the convergence rate, the idea of virtual force algorithm as the impact factor, is introduced into the coverage control algorithm based on bat algorithm, and then a new algorithm called Virtual Force-Bat Algorithm (VF-BA) is proposed. The virtual force factor directly influences on the distance and direction of mobile nodes according to the distance between the sensor nodes, which accelerates the uniform distribution of nodes. From the actual simulation results, it can be easily seen that the convergence rate has been significantly improved.The sensor nodes are small, and their power is limited. Once the energy is exhausted, wireless sensor network coverage holes will appear, which affect the performance of the network coverage. In the dynamic coverage problem, the energy consumption of sensor node contains the communication consumption and mobile consumption, and the mobile consumption is directly related to the moving distance of the nodes.Considering the influence of energy exhausted for the coverage performance of the network, the improved VF-BA based on energy limited is put forward. The algorithm limits the moving distance of the node, and reduces the energy consumption. According to the simulation analysis, the experimental data shows that the improved VF-BA based on energy limited has better performance than the original algorithm, which effectively extends the network lifetime, and ensure to complete the coverage task.In summary, the concept of bat algorithm is introduced to the coverage control algorithm in wireless sensor networks. The improved VF-BA based on energy limited is proposed step by step. The algorithm converges faster, effectively improves the coverage rate of the network, and extends the network lifetime, which achieves the purpose of the coverage optimization.At last, the end of the article is the summary of the work and the prospects for the future research.