光WDM网络中基于总波长和期望可用波长的自适应权函数路由算法

P. Pavarangkoon, N. Maneerat, R. Varakulsiripunth
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引用次数: 2

摘要

本文研究了波长路由(WR)光波分复用网络中的路由和波长分配问题。当给定会话请求时,路由和波长分配(RWA)的困难任务是计算两个节点之间的可满足路径,并沿着该路径分配一组可用的波长。为此,我们提出了一种新的路由和波长分配算法,称为总波长和期望可用波长(TEW)算法,以实现有效的路由和波长分配,保证对用户需求的服务。在TEW算法中,链路权函数是路由选择的主要因素。该函数是通过使用当前正在使用的波长数的确定因子来计算的,并且应该在一定时间后可用。使用Dijkstra最短路径算法,将用户的会话请求路由到链路权重最少的链路上。这意味着所选光路具有最小利用率和最大预期可用波长。通过计算机仿真并与传统机制进行比较,研究了所提出的链路权重计算函数对阻塞概率的影响。结果表明,本文提出的TEW算法在阻塞概率方面具有较好的性能
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Routing algorithms with adaptive weight function based on total wavelengths and expected available wavelengths in optical WDM networks
This paper studies routing and wavelength assignment in wavelength-routed (WR) optical WDM networks which are circuit-switched in nature. When a session request is given, the hard task of routing and wavelength assignment (RWA) is to calculate the satisfiable path between two nodes, and also to assign an available set of wavelengths along this path. Therefore, we have proposed a new routing and wavelength assignment algorithm, called total wavelengths and expected available wavelengths (TEW) algorithm in order to achieve the effective routing and wavelength assignment that can guarantee the service for user's requirement. The link weight function is considered as the main factor for route selection in TEW algorithm. This function is calculated by using a determination factor of the number of wavelengths that are being used currently and are supposed to be available after a certain time. The session requests from users are routed on the links that has the least number of link weights by using Dijkstra's shortest path algorithm. This means that the selected lightpath have the minimum utilization and maximum expected available wavelengths. The impact of proposed link weight computing function on the blocking probability is investigated by means of computer simulation and comparing with the traditional mechanism. The results show that the proposed TEW algorithm can achieve better performance in terms of the blocking probability
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