Genetic algorithm for optimal design of delay bounded WDM multicast networks

A. Jeyakumar, K. Baskaran, V. Sumathy
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引用次数: 5

Abstract

Multicast is an efficient way to distribute information from single source to multiple destination as well as many to many [Dr. A. Ebenezer Jeyakumar et al., Jan. 2003]. This paper shows the problem of real time delay bounded multicasting in wavelength division multiplexing network to avoid problem of synchronization between video and audio frames. This work describes a genetic algorithm based technique to synthesize wavelength division multiplexing (WDM) network topologies that can, with a high degree of confidence, assure that the multicast traffic is delivered in user specified limits on time. Unlike existing approaches to WDM network design, we first find a virtual topology that can meet the delay constraints. An embedding of virtual rings into physical links is then carried out, followed by an assignment of wavelengths to virtual links. The problem of finding the virtual topology is difficult because of a large number of parameters. A number of heuristic approaches have been proposed to solve such optimization problems. In this approach, the main aim is to explore the suitability of genetic algorithms to solve the WDM network design problem. A genetic algorithm can explore a far greater range of potential solutions to a problem than do conventional approaches. The advantage of a genetic algorithm, compared with other algorithms, which use a initial guess, e.g. gradient, descent is to use more information of estimation region, and to decrease the probability of falling into local minimum. This paper describes quantitative and qualitative results obtained by using our software tool on several benchmark examples.
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时延有界WDM组播网络优化设计的遗传算法
组播是一种将信息从单个源分发到多个目的地以及多对多的有效方法[Dr. A. Ebenezer Jeyakumar等人,2003年1月]。本文研究了波分复用网络中实时延迟有界多播的问题,以避免视频和音频帧之间的同步问题。这项工作描述了一种基于遗传算法的技术来合成波分复用(WDM)网络拓扑结构,该拓扑结构具有高度的可信度,可以确保多播流量在用户指定的时间限制内交付。与现有的WDM网络设计方法不同,我们首先找到一个可以满足延迟约束的虚拟拓扑。然后将虚拟环嵌入到物理链路中,然后将波长分配给虚拟链路。由于存在大量的参数,虚拟拓扑的查找问题非常困难。许多启发式方法已经被提出来解决这类优化问题。在这种方法中,主要目的是探索遗传算法在解决WDM网络设计问题中的适用性。与传统方法相比,遗传算法可以探索更大范围的问题潜在解决方案。与梯度、下降等初始猜测算法相比,遗传算法的优点是利用了更多的估计区域信息,降低了陷入局部最小值的概率。本文描述了用我们的软件工具对几个基准算例所得到的定量和定性结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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