Research On Barrier Coverage In Wireless Sensor Networks

With the rise of the concept of Internet of Things, as the infrastructure, wireless sensor networks attract increasingly interest of the researchers. Thanks to the rapid development of integrated chips, sensors, communications and many other technologies, wireless sensor nodes are enjoying reduced cost, multi-function, and prolonged survival time, which leads to the realization of multi-scenario, large-scale application of wireless sensor networks. Currently, wireless sensor networks are widely applied in the forest environment monitoring, smart cities, medical monitoring, military defense, and demonstration of many other industry, agriculture and forestry productions.The coverage rate, which reflects the monitoring capabilities of the interest indicators of the wireless sensor network deployment area, is one of the key metric of wireless sensor networks. Coverage control can improve the utilization efficiency of wireless sensor network resources, improve the network lifetime, thus energy-efficient coverage control algorithm is one of the most important research fields to build a wireless sensor network. Fence cover focuses on detecting of moving target through the detection area, the mobile track algorithms of smart moving path, experimental applications and etc. Fence covering has a great applicability potential in the field of border surveillance for forest fire prevention, industrial and agricultural production, and military counter-surveillance.Against the background above, this paper introduces the basic knowledge of wireless sensor networks and related definitions of wireless sensor networks barrier coverage, and summarizes existing research results. Aiming at the issue of appropriate moving path, after analyzing the deficiencies of the existing moving path algorithm, this paper proposes a AFMP (angle first moving path) algorithm which chooses the appropriate forward direction to generate moving path. Mathematical analysis and simulation results show that the AFMP algorithm requires neither global deployment information nor perception radius of sensor node, has a low sensitivity to node deployment density and distribution. Therefore, it is particularly applicable to the scenario where only the local node information is available. Besides, the complexity of the algorithm is also lower than Voronoi algorithm and the ideal grid algorithm.