Research On Energy-Efficient Coverage Optimization Of Wireless Sensor Networks

Wireless sensor network is composed of a large number of energy limited micro-sensornodes distributed in the monitoring regions, which have the sensing, computing andcommunicating capabilities through self-organized manner. Before the specific applications,the methods of deploying the sensor nodes should be determined according to the criteria ofapplication-specific environments. As one of the fundamental problems in the wirelesssensor network, the researches of coverage focus on the case that how to maximize thecoverage regions and achieve the reliable area observation with quality of service.Based on the problem of coverage, with the consideration of energy efficiency, thispaper discusses and researches energy efficient coverage optimization of wireless sensornetwork. The main research works are as follows:1. Energy-balanced coverage strategyTo solve the problems of coverage overlap、excessive energy consumption andcommunication conflicts caused by deploying nodes with high density, based on theselection of the optimal coverage set of nodes, an energy-balanced coverage strategy isresearched. A network of probabilistic sensing model is built and an energy balancecoefficient is set. Network coverage, working nodes and energy consumption coefficient arethe optimization goals, then the genetic algorithm is used to get the optimal coveragesolution. Simulation results show that the strategy can reduce and balance the energyconsumption while ensuring the high network coverage, thus making the network workstably and prolonging the network lifetime efficiently.2. Energy-efficient coverage optimization of dynamic nodesWhen used to solve the coverage optimization problem of dynamic nodes, PSO easilyfalls into the local optimum. So the coverage optimization based on disturbance-factor PSOis researched. The strategy adds a disturbance factor to the updating formula of PSO, thusguiding the evolution; Then, with the combination of quantum theory and PSO, thecoverage optimization based on QPSO is researched. The aggregation characteristic ofevery particle in the quantum space is unique, so the algorithm can search throughout theentire feasible region. Thus the QPSO, of which global search ability is much better thanPSO, can avoid the disadvantages of being easily trapped into a local extreme. Simulationresults show that the proposed algorithms are better than PSO in coverage optimization and the algorithm based on QPSO can eliminate the mean moving distance of the nodes, thusmeeting the aim of energy-efficient coverage.