Study On Multiple Coverage Scheduling Algorithm For Wireless Sensor Networks

Wireless sensor network (WSN) is a new multi-disciplinary crossed research field,composed of a lot of tiny sensor nodes which have ability of low power consumption,low cost, low computing and can communicate with each other to perform sensing anddata processing cooperatively in multiple hops manners. As a hot topic of the moderninformation field, WSN is widely used in military, environment, medical and otherfields.Network coverage control is one of the core technologies of wireless sensornetwork (WSN).Optimizing coverage control strategy not only guarantees the networkgood sensory quality to get completed and accurate physical information, but alsooptimizes the network space resources, reduces the network energy consumption andcost investment, and prolongs the network life. Due to the complexity of sensornetwork application environment, the sensor nodes can only be placed by a randomdeployment for a special environment like a forest or a desert, if the nodes work at thesame time, many redundant nodes will appear, and then the information data willcontain a large number of redundant data during transmission, hence the wholenetwork energy consumption will be increased. Therefore, to ensure the quality ofcoverage, redundant nodes will make into hibernation. This node scheduling policies isthe important optimizing ways of covering control.At present, most of the network coverage control strategy is on homogeneoussensor network research, rarely considering the network heterogeneity, there are a fewheterogeneous wireless sensor network coverage control algorithms for multiplecoverage, but they use Boolean model as the perception model, and ignore the nodeperception of uncertainty. This article is based on probability model as the node’sperception model to set up heterogeneous wireless sensor networks with nodesheterogeneous sensing radius and awareness of energy consumption per unit time, forthe existing "hot spot" areas of monitoring environment. Namely, in guarantee thehigh quality of "hot spot" areas coverage taking into account the entire networkcoverage requirements, in order to increase network coverage as far as possible andreduce network awareness of energy consumption per unit area per unit time,heterogeneous wireless sensor network node scheduling strategy that based on a nonlinear inertia weight and binary particle swarm multiple objective optimizationalgorithm is put forward.This algorithm uses the particle swarm algorithm to solve multi-objectiveoptimization problems. the particle’s fitness function is calculated by the Maximinvalue function, the fitness value is less than zero particles as a non inferior solution,and then using the dominations relation concentration in the non selected particleswarm of individual extreme and global extreme and introducing the deviation valueepsilon zero to the Maximin fitness function to calculate the fitness make betterparticle swarm toward the forefront of the Pareto solutions. Without prior knowledge,the algorithm can widely search in the decision-making space, and quickly find aheterogeneous wireless sensor network node scheduling strategy of Pareto optimalsolutions.Compared with the classical stochastic scheduling strategy and multi-objectiveoptimization algorithm based on the random weighted by a lot of simulation, thecoverage quality of sensor network of the algorithm that is proposed in this paper isbetter and more stable, and the algorithm reduces the network per unit area per unit timeawareness of energy consumption more effectively.