Dissertation > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation components,parts > Transmitter ( converter),the sensor > Sensor applications

Wireless sensor networks research TDMA slot assignment problem

Author DuanShaoMi
Tutor XiangFengHongï¼›MaoJianLin
School Kunming University of Science and Technology
Course Control Theory and Control Engineering
Keywords Wireless Sensor Networks TDMA Slot Allocation Catastrophic real-coded chaotic quantum-inspired genetic algorithm (CRCQGA) Routing
CLC TP212.9
Type Master's thesis
Year 2010
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Wireless Sensor Networks are constituted by lots of nodes of wireless distributed network. As the sensor technology, communication technology, computer technology and micro-electromechanical systems (MEMS) technology, the rapid development of wireless sensor networks because of its advantages such as non-center upsides, self-organization, located rapidly, and low cost and so on, is called after the following Internet the 21st century mankind will have a significant impact on lifestyle information technology.This paper studies the wireless sensor network time-division multiple accesses (TDMA) of the slot allocation problem, and using a variety of optimization algorithms to optimize the results compared. Which focused on the real-coded genetic algorithm for quantum chaos, quantum chaos for real-coded genetic algorithm for the characteristics of and to carry out a certain improvement in the precision of the issue, taking into account algorithms also take into account the algorithm program running time? Make the new real-coded genetic algorithm for quantum chaos is superior to other algorithms:either in a continuous test function, or in wireless sensor networks, TDMA time slot allocation optimization.Firstly, this paper introduce the status quo of the research, purpose and Meanings of the research, some basic concepts and main features of traditional Wireless Networks and Ad Hoc networks, performances and evaluation indexes and fields of application of WSNs.Secondly, this paper mainly presents quantum genetic algorithm (QGA). With the discussion of basic concepts, conventional quantum genetic algorithm and real-coded chaotic quantum-inspired genetic algorithm, analyze the relative merits of these two algorithms. This paper propose the catastrophic real-coded chaotic quantum-inspired genetic algorithm (CRCQGA), based on the continuous learning and accumulation of quantum genetic algorithm. Specific methods are adding convulsions to avoid premature, when the optimum solution is not changed in the given generations, retain the optimum solution and reproduce other individuals. Meanwhile, in the aspect of chaos sequence, compare the influences of algorithm of the chaos sequences based on different mapping model, change the logistic mapping model of the real-coded chaotic quantum-inspired genetic algorithm into Chebyshev mapping model. In the purse of bigger updating rate, which can help find the optimum solution in less time during the optimiziton of time slot assignment of wireless sensor networks time division multiple accesses, the algorithm has a different crossover operation and mutation operation in choice of individuals. In the traditional real-coded chaotic quantum-inspired genetic algorithm, individuals with good fitness do the crossover operation, individuals with bad fitness do the mutation operation; in the improved algorithm, population is divided into to parts, one half do the crossover operation, the other half do the mutation operation. Comparing the different algorithms in the continuous testing functions and optimization of Time Slot Allocation of Wireless Sensor Networks, CRCQGA has a better performance than the traditional real-coded chaotic quantum-inspired genetic algorithm.Third, the paper introduces two kinds of routing algorithms. Aboat the topology map to the same WSNs, it uses different routing algorithm and chooses a different transmission path, in the other words, it produces different routing tables, respectively, the different routing tables into the same optimization algorithm, to be falls far short of the optimization results show the impact the choice of routing wireless sensor networks TDMA-slot allocation results.Finally, conclusions and further research directions are given.

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