A Multi-Objective Optimization Algorithm for Routing Path Selection and Wavelength Allocation for Dynamic WDM Network using MO-HLO

Hamsaveni M, Savita Choudhary
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引用次数: 2

Abstract

The data transmission system in the optical WDM network increases the speed of packet transmission by the wavelength of light beams . The Selection of the wavelength and the shortest path to transmit the packets form source to destination is a challenge in a large network architecture. To solve these two problems, the optimization model must handle both the objectives. In this paper we are proposing a novel multi-objective optimization algorithm to solve both the problem of wavelength allocation and shortest path identification in a WDM network. This can be achieved by the enhanced model of Multi-Objective Hunger Locust Optimization algorithm (MO-HLO). In this, it analyse traffic level in a network path and the availability of wavelength present at each time instant. The proposed system retrieves the parameters of network architecture and with the weight value of dynamic traffic occur in the routing path. Among these data, the optimization selects the best among overall feature set of the WDM arrangement. The MO-HLO algorithm extracts the combination of each attribute to form the cluster that segregates the routing path along with the traffic range. From the fitness of the objective function of MO-HLO, the best routing path and the availability of wavelength for a node can be analysed at each time instant.
基于MO-HLO的动态WDM网络路由路径选择和波长分配多目标优化算法
光wdm网络中的数据传输系统通过光束的波长来提高分组传输的速度。在大型网络体系结构中,选择波长和最短路径将数据包从源传输到目的是一个挑战。为了解决这两个问题,优化模型必须同时处理这两个目标。本文提出了一种新的多目标优化算法来解决波分复用网络中的波长分配和最短路径识别问题。这可以通过多目标饥饿蝗虫优化算法(MO-HLO)的增强模型来实现。在这种情况下,它分析了网络路径中的流量水平和每个时刻存在的波长的可用性。该系统利用路由路径中发生的动态流量的权重值来检索网络结构参数。在这些数据中,优化选择WDM布置的总体特征集中最优的数据。MO-HLO算法提取每个属性的组合,形成集群,将路由路径与流量范围隔离开来。从MO-HLO目标函数的适应度出发,可以分析出每个时刻节点的最佳路由路径和波长的可用性。
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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