Barrier Covergae For Directional Sensor Networks

Directional sensor networks is a special form of wireless sensor networks with directional sensor nodes such as video sensors,micro microphones,radar, etc. Video, audio, image and other multimedia information can be collected. As the primary problem in wireless sensor networks,coverage control can optimize the allocation of temporal and spatial resources of networks. Barrier coverage is a sub problem of coverage control which focuses on the probability of being discovered when a moving target traverses through the monitoring region of sensor networks. At present, some research results have been accumulated in the traditional wireless sensor network barrier coverage control research. But the preliminary results have only been achieved in barrier coverage control of the directional sensor network. Therefore, it is urgent to study and research on the control algorithm of the barrier converge in the directional sensor networks. In this thesis, the following aspects about barrier coverage are studied.(1)The problem of strong barrier coverage in directional sensor networks composed of mobile sensors and stationary sensors is researched. When the sensor nodes are randomly deployed in the narrow band, there are a lot of overlapping sensing areas. It produces a large amount of redundant information which is not conducive to the effective utilization of resources. In this thesis, the concept of overlap-sense ratio(OSR) is introduced. The sensors in strongly-connected clusters after random deployment are adjusted based on OSR. Overlapping sensing areas are reduced. How to efficiently use mobile sensors to fill in gaps and form a barrier with stationary sensors is analyzed. The problem is transformed into the matching problem of weighted bipartite graph. And the improved Hungarian algorithm is used to solve it. Finally, the OSR-SBC algorithm is proposed. Simulation results show that the proposed algorithm significantly reduces the coverage overlap area. At the same time, the number of mobile sensor nodes and the distance of the mobile sensor are greatly reduced.(2)The problem of path coverage in directional sensor network is studied. Path coverage is known as art gallery problem which is a NP-hard problem. In this thesis, an improved particle swarm optimization(PSO) algorithm with a guiding factor of the nodes’ "neighbors set" coverage rate is proposed. Firstly, we transforms the path coverage model into optimization problem of seeking the optimal directions of nodes and the particle swarm algorithm is applied to solve the problem. Secondly,in view of the disadvantages of the standard particle swarm optimization algorithm, such as long convergence time, easily getting into the local optimum etc., the concept of nodes’ "neighbors set" coverage rate is put forward. It is used as a guiding factor to guide the evolution of particles to maximize the path coverage in the networks. At last, the performance of the algorithm is tested by simulations. The experimental results show that the improved particle swarm optimization algorithm can significantly improve the path coverage and overcome the shortcomings of the standard particle swarm algorithm.In summary, this thesis studied the construction of the strong barrier coverage and path coverage of the directional sensor network. And the effectiveness of the algorithm was verified by simulation experiments. The theoretical basis is provided for further research on the barrier coverage of the sensor networks.