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Research On QoS Multicast Routing Based On Genetic Algorithm

Posted on:2007-12-13Degree:MasterType:Thesis
Country:ChinaCandidate:W LiuFull Text:PDF
GTID:2178360185477594Subject:Operational Research and Cybernetics
Abstract/Summary:PDF Full Text Request
The rapid development of Internet and the widely used applications of multimedia technologies bring more and more challenges to routing algorithms and need more and more strict requirements. Different kinds of applications need different QoS guarantees, and there may be some relationship or even contradiction between QoS objectives, all of these increase the complexity of routing optimization. In addition, the inaccuracy of network state information will have unexpected impact on the performance of routing algorithms. Therefore the researches on routing algorithm that can optimize one or more objectives simultaneously or can deal with the uncertain network state information become a significant aspect of the study of routing algorithms.The thesis is composed of five parts. The first part introduces the background of QoS multicast routing. Then the second part classifies the routing algorithms, mainly analyzes unicast routing and multicast routing, summarizes associated classic algorithms, and provides a good theory foundation of multicast routing. In the third part, multi-objective optimization algorithms of QoS multicast routing are proposed, and four methods are used in the process of evolution: the adaptive weight approach uses the useful information in the current population to readjust the weights and increases the speed of convergence. The random weight approach creates weights randomly, makes the algorithm search in alterable directions, samplings uniformly along Pareto-optimal Front, and increases the success rate. The Pareto ranking approach assigns the fitnesses in a reasonable way, makes the Pareto solution have same fitnesses, and can adjust the pressure of selection. The Pareto tournament approach maintains the diversity of the population by fitness sharing, and improves the performance of the genetic algorithm. In the fourth part, a genetic algorithm based...
Keywords/Search Tags:Multicast Routing, Genetic Algorithm, QoS(Quality of Service), Multi-objective Optimization, Pareto Optimal Solution, Inaccurate Information
PDF Full Text Request
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