Target Coverage Problem Research Based On Probabilistic Sensing Model In WSN

In the research field of Wireless Sensor Networks,coverage problems can be divided into three categories: target coverage,area coverage and barrier coverage.In the existing study of coverage problems,the researchers mostly use 0/1 coverage model.It is considered that the target can be covered by the sensor as long as it is in the sensing range of the sensor,and it will not be monitored by the sensor when the target is outside the sensing range of the sensor.In recent years,researchers have proposed the probabilistic model which is more practical,and can more accurately depict the coverage quality of the sensor.The probability sensing model considers that the probability that sensor monitor the target decreases when the distance between the two increases.Due to the uncertainty in monitoring of probabilistic sensing models,a target may require joint monitoring of multiple sensors to meet the coverage requirements.However,only one sensor could meet the target coverage requirements in the 0/1 coverage model.In this case,some of the algorithms proposed in the coverage problem based on 0/1 model are no longer applicable to the probability model.We need to design a new theory system and algorithm to solve the coverage problem in the probability sensing model.In this paper,we first study the maximum lifetime of sensor networks under omnidirectional probability sensor with adjustable sensing radius.We combine the probability sensing model with the adjustable sensing radius,and propose the multiple network coverage set problem under the omnidirectional probability sensor with adjustable sensing radius(PARMCS)for the first time,which aims at scheduling a set of sensors with limited energy and adjusting its sensing radius to generate multiple network coverage sets.These network coverage sets are activated in turn to cover all the targets in order to maximize the lifetime of the sensor network.We prove that the problem is a NP-complete problem,and it is impossible to obtain its optimal solution in polynomial time.So two heuristic algorithms are designed to solve the suboptimal solution of the problem,and the performance of the two algorithms is verified by a large number of simulation experiments.In order to reduce the cost of production and save energy,the researchers put forward a directional sensor.Its sensing direction can be adjusted,and it is no longer a 360 degree omnidirectional monitor,it only detects one sector area.Based on this model,then we study the maximum lifetime of sensor networks under directional probability sensor with fixed sensing radius.We combine the probabilistic sensing model with the directional sensor,and propose the multi network coverage set problem(DPMCS)bosed on the directional probability sensor with fixed sensing radius for the first time,which aims at scheduling a set of sensors with limited energy and adjusting its sensing direction to generate multiple network coverage sets.These network coverage sets are activated in turn to cover all the targets in order to maximize the lifetime of the sensor network.We prove that the problem is a NP-complete problem.So a heuristic algorithm is designed to solve the problem,and the performance of the algorithm is verified by a large number of simulation experiments.