Research On Node Deployment And Coverage Control In Directional Wireless Sensor Networks

Coverage problem as a fundamental problem in sensor networks, research on how to optimize the node deployment, so as to achieve optimal network coverage performance. Reasonable node deployment not only ensure the network coverage and connectivity, but also extend the lifetime of the network.This paper deeply studies coverage sensor network coverage enhancement algorithm and sink deployment issues in random deployment directional sensor network(DSN). The main research work are as follows:According to the issue of sink deployment problems in random deployment directional sensor networks,a multiple sink deployment algorithm based on clustering partition(CDMSDA) is proposed. By greedy algorithm, K of the sink node position was found, to ensure the distance between all the normal nodes and the sink within one jump communication. Divide the nodes into K clustering. Considering the monitoring area may have isolated nodes,which will lead to unnecessary sink deployment costs, adding mechanism of merger in clustering process. Through the cycle of clustering for many times, finally found optimal number of sink node and their deployment position,which make the distance between nodes and sink is shortest.Simulation experiments show that CDMSDA algorithm is better than RDF algorithm in the deployment number of the sink node and their position, also can promise the average distance between ordinary nodes and sink within one jump communication. so as to prolong the lifetime of the network.According to the issue of coverage enhancement problem in directional sensor networks, a coverage enhancing algorithm for directional sensor networks is proposed, which is so-called virtual force-directed particle swarm coverage-enhancing algorithm(VFPSC-DSN). Aiming at maximize the efficient coverage of networks, VFPSC-DSN combines virtual force with particle swarm optimization algorithm. In the algorithm, velocities of the particles is updated according to not only historical solutions and global optimal solutions but also the virtual force between the centroid of the nodes. The key point of this scheme is to use virtual force to direct the updating of particle swarm algorithm for enhancing the convergence speed, and particle swarm optimization algorithm is used to improve the global searching ability. By adjusting the main sense direction nodes, the network coverage optimization is achieved. Simulation result shows that VFPSC-DSN solving the coverage problem of directional sensor networks efficiently and rapidly.