Algorithm Research On Coverage And Node Redundancy In DSNs

With the diversification and complexity of monitoring tasks in detecting area,more comprehensive and abundant environmental data(such as video,image,infrared,etc.)are needed to get.Thus directional sensor networks is generated.In practical applications,sensor nodes in the directional sensor networks are usually composed of a video sensor,an infrared sensor or an ultrasonic sensor with directional perception.Because of the extremely bad environment,unreachability of the staff and the redundancy of sensor nodes in the detecting area,the problem of perceptual overlapped and coverage hole of sensor nodes will be generated when the sensor nodes are random deployed in a large-scale directional sensor networks.Therefore,the perceptual direction of the sensor nodes have to be adjusted after initial deployment to enhance the coverage of the detecting area.The resource utilization of the directional sensor networks is improved,and the life cycle of the networks is prolonged,then the quality of service is finally raised.In the research of existing coverage enhancement strategies and algorithms for directional sensor networks,the research on network coverage enhancement based on particle swarm optimization,fish swarm algorithm,genetic simulated annealing algorithm and other bionic algorithms are much more,but thesealgorithms are of high complexity and slow convergence.In this thesis,in view of the shortcomings of the above network coverage enhancement strategies,a novel distributed coverage-enhancing algorithm,Iterated Weighted Resultant Force of Grid Points(IW-RFGP)is proposed by studying the characteristics of large-scale random deployment of nodes in directional sensor networks,analyzing the problem of the perceptual overlapped and coverage hole and based on the direction adjustable of sensor nodes in directional sensor networks.In this algorithm,the sensing area of each sensor node in the directional sensor networks is discretized.The centroid of the area that is not covered by any neighbor node is determined by the resultant force of the iterated weighted attraction of discrete grid points,and the new perceptual direction is determined to enhance the coverage rate of the whole detecting area.Secondly,aiming at the problem of sensor node redundancy after coverage enhancement strategy in directed sensor networks,a discrete mesh redundant node scheduling algorithm(DM-RNSA)is proposed.In this algorithm,overlapped rate of perceptual coverage between the sensor node in the networks and neighbor nodes of this sensor node is calculated after coverage enhancement strategy.The sensor nodes with high overlapped rate and relatively small number of adjacent nodes are selected to enter the dormancy state.In this way,the communication burden of neighboring nodes and the overall energy consumption of directional sensor networks are reduced.The simulation results show that the convergence speed of the IW-RFGPalgorithm is fast,and the new sensing directions of sensor nodes in the directional sensor networks can be determined in less iterations,and the coverage rate of the directional sensor networks can be effectively enhanced.In DM-RNSA algorithm,the number of redundant nodes in the directional sensor networks and the energy consumption of the whole networks can be effectively reduced.