Wireless Sensor Optimization Algorithm Based On QGA

Wireless sensor network have concentrated distribution information handling technology, perception technology, electrical technical, embedded computer technology with wireless communication technology, which get a new kind of information acquisition and handle pattern. Because of its powerful information handling ability and communication ability, wireless sensor network have extensive application prospect. Which can extensively apply in military defence, environmental inspection, Medical Protection and space explore, the long-range control of dangerous area and so on. In wireless sensor network the layout and overlay of nodes, network communication agreement and node location are some basic problems in sensor network research. In which, nodes location have important role in wireless sensor network, such as the application of wireless sensor network, operation and management , are also the one of hot problem in sensor network research.Therefore this paper introduce the domestic and international research present situation, major characteristic, advantage and performance appraisement index etc. based on wireless sensor network location technology firstly.Node location is the important content in wireless sensor network, and location technology is the core that supports this important content ,In second chapter ,this chapter emphatically introduce basic concept with state language, node location calculation and the classification of location algorithm have made detailed introduction for the existing domestic and international node location algorithm of Centroid location algorithm, protruding program location algorithm, DV-Hop location algorithm, DV-distance algorithm, APIT algorithm, AHLos location algorithm and n-hop multilateration primitive location algorithm that has representative in wireless sensor node locationThere are their advantages these algorithms of introduction before, but they have a common point that make sensor node location information fall into partly optimal solution , but genetic algorithm and quantum genetic algorithm are the method based on probability, they do not be easy to fall into partly optimal solution, the result of optimization has very strong robustness. Therefore, genetic algorithm and quantum genetic algorithm are introduced emphatically in the 3rd chapter, and the basically operation and the process of genetic algorithm are introduced in detail, which have made good pad for the 4th chapter.Based on the node location method part of quantum genetic algorithm have established goal function and have given fitness value calculation , have written detailed algorithm structure and its process, have made clear the termination condition of algorithm , and have made emulation.Finally, this paper has given the conclusion and summary of full text, and has stated the direction of the research in the future.