【作者】 楼小明；

【导师】 王万良； 包中文；

【作者基本信息】 浙江工业大学 ， 计算机技术， 2009， 硕士

【摘要】 网络技术的飞速发展远远不能满足媒体业务发展的需求。网络传输的业务不仅包括文本数据信息,还包括语音、图形、图像、视频、动画这些类型的多媒体信息。QoS(Qualityof Service)的概念被用来描述服务提供者和用户应用程序之间的性能约定。QoS需求体现为一系列网络约束条件,如链路约束,路径约束或树约束。因此QoS路由问题可以归结为寻找路径或树在满足约束条件的同时,优化某种特定的代价函数。本文的主要工作和成果如下:1.针对QoS组播路由的选择与优化问题,提出了一种基于蚁群算法寻找最优组播树的策略,即通过使用最小生成树导向的蚁群算法求解到各个目的节点的单播QoS路由问题时,巧妙地利用多个蚂蚁的全部爬行线路创建备选路径集,利用基于备选路径集的编码方式建立组播路由问题的整数规划模型,然后利用蚁群算法求解出最优组播树,并通过仿真实验加以了证实。2.本文首先从QoS的概念出发,详细阐述了目前在QOS组播路由中存在的问题,研究了基于QoS的路由算法,提出了蚁群优化是一种用于求解复杂组合优化问题的启发式方法。本文对几种常见的蚁群优化算法进行了比较、分析和研究,对该几种算法进行了性能比较。而且总结了各蚁群优化算法中普遍存在的两个缺陷,即算法容易停滞和算法收敛速度较慢。基于现有蚁群算法提出了一种新的解决QoS组播路由问题的思路,新算法在寻找较优解和提高算法收敛速度两方面取得了较好的效果,仿真实验结果表明新算法的求解性能较优。3.本文所述算法尽管是在随机生成的网络上进行了的QOS组播路由的应用,仍然与实际相距甚远,在以后还有大量的工作需要完成,需要继续更深入的研究蚁群优化算法及其最新的发展,通过与其他算法法的组合,来更好地解决QOS组播路由的优化问题。更多还原

【Abstract】 The rapid development of the network technology is far from satisfying the tremendous demands of multimedia businesses. Network not only transmits data messages, but also kinds of multimedia messages like sound, graphics, video, animation. The notion of Quality of Service (QoS) has been proposed to describe the quality defined performance contract between the service provider and the user appilcations. The QoS requirement of a connection is given as a set of constraints, which can be link constraints, path constraints, or tree constraints. So the QoS routing problem can be attributed to the construction of path or tree which satisfies the end-to-end QoS constraints at the same time optimizes somes pecial cost function.In this paper, the main work and achievements are as follows:1. About the selection and optimization problems of QoS multicast routing ,this paper proposed to find the optimal strategy for multicast tree which is based on ant colony algorithm, namely, through the use of minimum spanning tree-oriented ant colony algorithm to each destination node unicast QoS Road by the issue, the clever use of multiple lines of ants crawling all set to create alternative paths, using alternative paths based on the set coded approach to building multicast routing problem in integer programming model, and then use ant colony algorithm for the optimal group of multicast tree, and through simulation experiments to be confirmed.2. In this paper, starting from the concept of QoS in detail at the current Qos Multicast Routing Problems, research-based QoS routing algorithm, ant colony optimization is used for solving a complex combinatorial optimization problem inspired approach. Ant Colony Optimization (ACO) is a metaheuristic approach for solving hard combinatorial optimization problems.This thesis introduces the general development of ACO. Some analyses and remarks are made to compare the performance of some typical ACO algorithms. Additionaly, Two main disadvantages of ACO are also concluded, that is, stagnation and slow-convergence. An adaptive ant colony system algorithm is proposed to solve the QoS routing is proposed. Through dynamically adjusting the interaction among ant colonies, the stagnation of the new algorithm is effectively mitigated.The analysis and the experimental results show that the new algorithm can achieve better performance.3. Algorithm described in this article, albeit in a randomly generated network carried out the QOS multicast routing applications, remained far away from the actual, in the future there is a lot of work to do, need to continue more in-depth study of ant colony optimization algorithm and its latest developments, through a combination of law and other algorithms to better address the QOS multicast routing optimization problem.更多还原