Research On Coverage Algorithm In Directional Sensor Networks

The coverage in wireless sensor networks is a fundamental problem. A series ofachievements have been made in the study of coverage control for omnidirectional sensornetworks. However, with the development of directional sensor nodes, the existingcoverage control method fails to apply. In this paper, we address the problem of coveragecontrol in directional sensor networks with random distribution, and have in_depthresearch on the quality of coverage and targets under monitored.First, we study the quality of coverage based on exposure path in directional sensornetwork. We define the sensing model of directional sensor and exposure model. Then thecontinuous path is transformed into a discrete problem by the grid segmentation. On thebasis of this, an algorithm simulating the path of invaders based on Markov Chain isproposed, looking for the exposure path of the sensor network, especially the minimumexposure path. We also design a model of HMM for self learning on movement pattern oftargets. The algorithm is applicable under the condition of the given any distribution,density and network features of the sensor nodes.Then we study the full-view coverage problem in directional sensor network. Thefull-view coverage ensures that the positive images of targets are obtained. In existingworks, the topics only focus on whether a region is full-view covered or not, which needstoo many nodes, and is less flexible for the change of surveillance environment. Therefore,full-view coverage for the targets is highlighted in this paper. Firstly, we derive theoptimal observation angle between the sensing direction of nodes and the vector of targetsurface. We also prove that the full-view coverage is a NPC problem. Then the centralizedand the distributed algorithms are proposed to maximize the number of full-view coveredtargets by scheduling the sensing directions of some sensors in the network.Finally, we design a simulation experiment to verify the correctness of the algorithm.The results show the exposure path can effectively to metric the coverage quality of thesensor network, which is important for the network deployment, and is helpful to improvethe monitoring quality of targets. Results also show that local adjusting of the directionalnodes will increase the full-view coverage for the global monitored objects with random deployment.