Algorithm Research And Design On Sweep Coverage In WSN Based On Clustering

With the continuous development and maturity of wireless sensor technology, Wireless sensor network(WSN) attracts great attention due to its broad applications in a lot of fields, such as environment monitor, military affairs, medical and health care, and so on. Coverage control is the important measure of quality of service, which reflects the sensing quality provided by WSN. It also can promote the utilization of network resources. In recent year, Sweep Coverage is one hot issue of coverage control in WSN. In the research of Sweep Coverage, with the reason that points of interest(POIs) must be monitor periodically, we use mobile sensors to complete the scanning task. So, the challenging problem of Sweep Coverage is how to schedule minimum number of mobile sensors to achieve specified sweep period. Sweep Coverage can reduce unnecessary extra overhead in the application of patrol inspection. Now, Sweep Coverage is still an open research topic. Thus, the research on Sweep Coverage in WSN has its academic and practical value.This paper makes a further research for Sweep Coverage. The main contributions of this paper are summarized as follows:①Analyzing the disadvantage of the related research results, we propose a two-tier model for Sweep Coverage, which includes data sensing and data transmission. In the same time, we form the goal of this paper: with the requirement of coverage period, using the minimum MobileSweep and MobileSink covers the whole WSN.②Based on the model of Sweep Coverage, we propose the method for the problem:1) In the phase of data sensing, we divide WSN into several clusters using the method of subtractive clustering based K-means clustering algorithm, which ensures that POIs with close range in the same cluster and the POIs with long distance in the different cluster. 2) Finding the optimal path of scanning POIs in the same cluster with Genetic algorithm(GA). Then, analyzing the minimum number of MobileSweep. 3) In the phase of data transmission, we choose the appropriate position for storage nodes firstly, then finding the optimal path of scanning storage nodes with GA too. Then, analyzing the minimum number of MobileSink.③We implement the algorithm proposed by this paper. Then, we conduct simulation experiments with Matlab and compare with MinExpand to verify the feasibility of our algorithm.In summary, with the goal of reducing extra overhead and ensuring information timely delivered, we discuss Sweep Coverage problem in data sensing and data transmission and solve the problem using optimization algorithm. Our works have their academic and practical value on promoting the advancement of the researches and applications in WSN.