Coverage Enhancement Method Based On Probabilistic Model For Wireless Sensor Networks

With the development of mobile Internet technology and sustained improvement in scienceand technology,wireless sensor networks(WSNs) consisting of sensor nodes is increasinglywidely applied to practice,which also has gradually achieved the low-cost, low-power,high-efficiency goals.However, how to maximize network resource utilization is still the problemneeds to be solved.Coverage control problem in WSN is an issue which concentrates on how tooptimize allocation of resources, increase coverage area and extend lifetime according toscheduling algorithm and self-regulation. Therefore, related reserch on how to maximumcoverage using minimum consumption and make full use of various resources will become amajor subject.In this dissertation, a full investigation of the existing domestic and international literature onwireless sensor networks has been done, research work on the coverage control problems hasbeen focused on and summarized. Based on these works, the proposed method improves theexisting algorithm, and the main contributions are described as follows:(1) Firstly the probability model is introduced into the coverage-enhancing algorithm of thedirectional sensor network based on the virtual potential field, and the probability model wouldhave an impact on the location of the centroid. Secondly, to the boundary coverage, through thesimulation of typical algorithms which consider the boundary repulsion, it finds that the coveragerates of the corners are much lower than the overall coverage. To add a vertex force on the corneris essential and to some extent would reduce the gap between them. Finally, based on the randomdeployment of sensor nodes, a novel algorithm are proposed which determines whether the sensornode rotate or move along fixed direction according to the coverage effect, named as PRMCA(Probability model based Rotate or Move along fixed direction Coverage-enhancing Algorithm).(2) In the coverage enhancement algorithm based on the path of a moving targetMTPCA(Moving Target based Path Coverage-enhancing Algorithm), sensors can detect theposition information of the target node in real time, MTPCA discretize the target moving path,and by adjusting the angle of the sensor nodes to coverage the points on the curve. In theoverlapping area, whether the sensor is active or not can be determined by the sensing nodeselection criteria.This dissertation verify the effectiveness and the practicability of PRMCA algorithm and MTPCA algorithm respectively by comparing them with other algorithms in simulationexperiments.