Deployment Algorithm For Underwater Wireless Sensor Networks

With the development of social economy, the progress of science and technology resources, the increasingly serious energy problems, explore and discover new energy has become particularly urgent. As the surface morphology and structure of the earth ocean area is the most widely, the research is also more and more attention. In order to better complete the ocean target monitoring and information acquisition tasks on water wireless sensor network(Underwater Wireless Sensor Networks, UWSN) has become a hot research. The underwater wireless sensor network deployment and coverage problem is directly related to the communication bandwidth, node power, optimal allocation of computing power and other limited resources, also affect the communication, monitoring the perceived quality, and other services.First, this paper briefly introduces the research background and significance of the underwater wireless sensor network, system structure, introduces the wireless sensor network at home and abroad research status, and a detailed description of the research status of UWSN deployment. The UWSN coverage classification method according to the application coverage of the object classification, there are three, coverage, barrier coverage, coverage area. Nodes of a three kinds of perceptual model, 0-1 sensing model, probability and directional sensing model, and focuses on the probabilistic sensing model.Secondly, the deployment of the underwater sensor based on virtual force is introduced, and the grid is divided into the target area. The algorithm is simulated, and the results are analyzed.Again, in genetic algorithm based on combined with virtual force method, while considering the target water body and the average energy consumption of, of a virtual force oriented Genetic Algorithm of energy balance deployment strategy. Node probability sensing model is constructed, through grid partition method for estimation of coverage, the strategy by using the genetic algorithm to control the number of mobile sensor nodes. In addition, the use of the semi deterministic deployment method and random deployment method as control, and try to use the geneticalgorithm toolbox of the University of Sheffield and verify two different genetic algorithms on the network to the influence of the similarities and differences.Finally, the definition of "degree" of the concept, and based on the "degree". The experimental simulation of the 2D and 3D environment. Underwater mobile wireless sensor network deployment analysis, to reduce the number of mobile nodes, saves energy, prolongs the network survival. On the basis of the "degree" of the proposed 3D underwater sensor networks of separate deployment strategy, although not to improve the coverage, but easy to implement, can reduce capital investment and with the progress of science and technology may also is the underwater wireless sensor network deployment of one.In addition, the research of this paper is analyzed, and the future research work is prospected.