Swarm Intelligence Algorithm And Its Application In Layout Optimization Of WSN

In the Wireless Sensor Network (WSN) technology research, the Sensor layoutoptimization problem is the focus，and the network life cycle and the coverage are thetwo important factors needed to be considered.The intelligence optimizationalgorithm is used in the sensor layout optimization to realize the network life cycleand the coverage maximization. Firstly, the particle swarm optimization (PSO)algorithm and the artificial fish swarm algorithm (AFSA) are applied to the WSNcoverage optimization problem to improve the coverage. Then, the ZigBee technologyis taken as the research object, and the mine location system based on ZigBeetechnology is applid for research background. The AFSA is used to optimize theanchor nodes arrangement, in order to reduce energy consumption and prolong thenetwork life cycle. The detailed research work is as follows:1．In this thesis, the basic principles and application of the swarm intelligenceoptimization algorithm are given detailed analysis, and the PSO and the AFSA aretaken as the main research objects. The basic idea of the artificial fish algorithm, theartificial fish model, four basic behaviors and the realization of the algorithm processare given thoroughly introduces. And then makes a detailed account on the standardparticle swarm algorithm’s principles, parameters setting, the implementing steps andthe improvement of the particle swarm algorithm. Finally the benchmark functions areused to test the optimization performance of the particle swarm algorithm and theartificial fish algorithm.2．The coverage classification and the mathematical model of wireless sensornetwork are mainly introduced in detail. The PSO and the AFSA are respectively usedin wireless sensor network coverage. The simulation results show that the artificialfish algorithm has better optimization effect.3．ZigBee technology as a representative of wireless sensor network is made adeep research in this thesis, and its characteristics, agreement basis and networktopology structure are mainly introduced. An optimal strategy based on two-tieredanchor nodes placement are proposed. Simulation results show that the improvedanchor nodes placement strategy provide significant benefit over the two commonlyuniform placement scheme. The AFSA is used in the anchor nodes layout, andcompared with the two-tiered anchor nodes placement method, the experimentalresults show that the AFSA obviously outperform the two-tiered scheme in terms ofboth network lifetime and average energy consumption.