Research On Point Coverage Technology For Wireless Sensor Networks

Wireless sensor networks are such kind of integrated wireless networks which perform sensoring, data processing, storage and delivering. There are wide applications for the networks in both military and civil affairs. The coverage problem is one of the important issues in wireless sensor networks and reflects the quality of service. With the energy constraint, one main requirement of the coverage problem is to find a small subset of sensor nodes such that this subset can independently perform the required tasks while other redundant nodes enter into the low energy sleep status.At present, researchers stress the central optimize algorithm which restrict practicality use to solve the point coverage problems. By exploring new application scenario in the point coverage issues, this dissertation aims to the point coverage problems to research the relevant algorithms based on Boolean sensoring model. Considering the restriction of the object distribution to the connectivity, this dissertation also studies the connected coverage problems to put forward a relevant algorithm.This dissertation first discusses the redundant nodes scheduling mechanism for wireless sensor networks. Furthermore, a distributed algorithm SRCA is put forward in the dissertation. This algorithm checks the redundant nodes in the network to make the redundant nodes sleep such that the redundant nodes are reduced obviously in the network. SRCA can effectively reduce the energy expense so to prolong the network lifetime.Toward an application scenario, this dissertation proposed a sensor node approximately scheduling algorithm NSAGA based on genetic algorithm. This algorithm utilizes the population characteristic to solve the coverage subset. NSAGA can not only produce a few of coverage subsets to satisfy the coverage requirements in an iterative but also suit to diverse application scenarios by changing the restriction according to the coverage requirement.Nowadays, the algorithms translate the point coverage problems into mathematic programming models, and then solve the mathematic programming by the central approximate algorithm. Although the method is of better precision, it is unsuitable for the large wireless sensor network. Therefore, this dissertation proposed a method to localize central algorithms, then a distributed algorithm LCACA is put forward. LCACA first elects the local central nodes to divide the network into a few of small scale subnets. Then, the central algorithm can be performed in these subnets. The algorithm can perform different scheduling algorithms in wireless sensor networks according to the sub-area coverage requirement.Since current point coverage algorithms which are proposed in case of coinciding the coverage with connectivity ignore the influence of the object distribution over connectivity. A central algorithm CCAST based on Steiner tree is proposed. CCAST first translates a connected cluster into a virtual node. Then, it constructs a weighted graph and calls current algorithm to pick out nodes which connect the network. Furthermore, a distributed algorithm DCAVIS is proposed. The algorithm first constructs a virtual independent set, and then finds out relay nodes.In summary, aiming at the point coverage issues, this dissertation discussed the point coverage problem in the distributed algorithm, central algorithm and the method to localize the central algorithm. The method to localize the central algorithm can be further exploited for future research.