A Multi Objective Evolutionary Algorithm Based Approach for Traffic Grooming, Routing and Wavelength Assignment in Optical WDM Networks

T. De, Puneet Jain, A. Pal, I. Sengupta
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引用次数: 2

Abstract

In the wavelength division multiplexing (WDM) optical networks, user's requirement is much less (in Mbps range) than the capacity of a wavelength channel (in Gbps range) and number of wavelength channels is limited in a fiber due to several constraints. Each wavelength channel between end nodes requires a pair of transmitter and receiver for digital to optical conversion. In order to decrease the cost of network resources (bandwidth, transceivers, etc.), it has become necessary to groom or multiplex traffic request efficiently over the given network topology. Most of work found in the literatures focus on single objective either maximize throughput or minimize transceivers or delay. In this study, we have presented a multi objective evolutionary algorithm (MOEA) based approach which is capable of optimizing multiple objectives i. e. throughput, transceiver requirement and intermediate propagation delay simultaneously. The performance of our approach has been evaluated through extensive simulation on different sets of traffic demands with different bandwidth granularities under various network topologies. The efficacy of our proposed approach has been established by comparing its performance with respect to existing algorithms.
基于多目标进化算法的WDM光网络业务量疏导、路由和波长分配方法
在波分复用(WDM)光网络中,用户的需求(在Mbps范围内)远远小于波长通道(在Gbps范围内)的容量,并且由于多种限制,光纤中波长通道的数量受到限制。端节点之间的每个波长通道都需要一对发送器和接收器进行数字到光的转换。为了降低网络资源(带宽、收发器等)的成本,有必要在给定的网络拓扑结构上有效地训练或复用流量请求。文献中发现的大多数工作都集中在单个目标上,要么是最大吞吐量,要么是最小收发器或延迟。在本研究中,我们提出了一种基于多目标进化算法(MOEA)的方法,该方法能够同时优化吞吐量、收发器需求和中间传播延迟等多个目标。通过对不同网络拓扑下不同带宽粒度的不同流量需求集的广泛模拟,我们的方法的性能得到了评估。通过与现有算法的性能比较,我们提出的方法的有效性得到了证实。
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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