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Coverage Optimization Of Wireless Sensor Networks Based On Chaotic Quantum-behaved Particle Swarm Algorithm

Posted on:2017-02-15Degree:MasterType:Thesis
Country:ChinaCandidate:W WangFull Text:PDF
GTID:2348330488980048Subject:Computer application technology
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In recent years,significant progress has been made towards the modern technology and information networks,the developing upsurge of the Internet of Things(IOT)is appearing and getting more attention from both academy and industry of different countries.As the important composition structure of perception layer,the research and design on Wireless Sensor Networks(WSN)receives more and more attractive.The coverage rate,is an important scale index in the design of a Wireless Sensor Network.Thus,those,how to reach a large-range cover in object region with limited sensor nodes while reducing nodes power consumption and prolonging the network lifetime at the same time,are of important research value,and hot issues of wireless sensor networks.Since 1980 s,swarm intelligence algorithm,as a relatively new method of optimal calculation,has been closely focused and widely researched.Particle Swarm Optimization(PSO)is a heuristic search method based on swarm intelligence,and has been heavily used to solve various problems in engineering fields.Due to its simple,tending to realize,few adjustable parameters,fast convergence speed and so on,the algorithm with wide application in solving combinatorial optimization problems has increasingly evident advantages.The conventional PSO algorithm has its own shortages of low convergence speed,sensitivity to local convergence in solving problems of the WSN coverage rate.To address these problems,based on the combined utilization of quantum-behaved particle swarm algorithm and logistic chaotic map,a hybrid optimal algorithm(chaos quantum-behaved particle swarm optimization,CQPSO)is proposed.Judging the local convergence by the variance of the elite individuals' fitness during the iterative process of optimization,the algorithm can improve the search's efficiency,solving precision,and keep the diversity of the population.Coverage control problem could be treated as a combinatorial optimization problem in many ways.Taking the network coverage rate as the optimized goal,this paper uses the CQPSO algorithm which can obtain the better optimal effect in solving combinatorial optimization problems to study random coverage optimization problem.The movement of every reasonable to sensor nodes so that their position distribution will be more uniform,thus not only reduces the network redundancy,but also the energy consumption caused by the movement of nodes.Simulating results show that the proposed algorithm is superior to other algorithms(namely PSO,QPSO and CPSO algorithm)on the coverage rate,network evenness and average traveling distance,and then,the reliability and validity of the algorithm is proved by practical examples.
Keywords/Search Tags:Wireless Sensor Networks(WSN), chaos searching, QPSO, coverage optimization
PDF Full Text Request
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