Routing, Modulation Level, and Spectrum Assignment in Elastic Optical Networks—A Serial Stage Approach with Multiple Sub-Sets of Requests Based on Integer Linear Programming

IF 1.9 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Luis Víctor Maidana Benítez, Melisa María Rosa Villamayor Paredes, José Colbes, César F. Bogado-Martínez, B. Barán, D. Pinto-Roa
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引用次数: 0

Abstract

This paper addresses serialized approaches of the routing, modulation level, and spectrum assignment (RMLSA) problem in elastic optical networks, using multiple sequential sub-sets of requests, under Integer Linear Programming (ILP). The literature has reported two-stage serial optimization methods referred to as RML+SA, which retain computational efficiency when the problem grows, compared to the classical one-stage RMLSA optimization approach. However, there still remain numerous issues in terms of the spectrum used that can be improved when compared to the RMLSA solution. Consequently, this paper proposes RML+SA solutions considering multiple sequential sub-sets of requests, split traffic flow, as well as path-oriented and link-oriented routing models. Simulation results on different test scenarios determine that: (a) the multiple sequential sub-sets of request-based models improve computation time without worsening the spectrum usage when compared to just one set of requests optimization approaches, (b) divisible traffic flow approaches show promise in cases where the number of request sub-sets is low compared to the non-divisible counterpart, and (c) path-oriented routing succeeds in improving the used spectrum by increasing the number of candidate routes compared to link-oriented routing.
弹性光网络中的路由、调制电平和频谱分配——基于整数线性规划的多请求子集串行阶段方法
本文讨论了在整数线性规划(ILP)下,使用多个顺序请求子集的弹性光网络中路由、调制电平和频谱分配(RMLSA)问题的串行化方法。文献报道了称为RML+SA的两阶段串行优化方法,与经典的一阶段RMLSA优化方法相比,该方法在问题发展时保持了计算效率。然而,与RMLSA解决方案相比,在所使用的频谱方面仍然存在许多可以改进的问题。因此,本文提出了RML+SA解决方案,考虑了多个顺序请求子集、分流流量以及面向路径和面向链路的路由模型。不同测试场景的仿真结果表明:(a)与仅一组请求优化方法相比,基于请求的模型的多个顺序子集在不恶化频谱使用的情况下提高了计算时间,以及(c)与面向链路的路由相比,面向路径的路由通过增加候选路由的数量来成功地改进所使用的频谱。
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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来源期刊
Mathematical & Computational Applications
Mathematical & Computational Applications MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
自引率
10.50%
发文量
86
审稿时长
12 weeks
期刊介绍: Mathematical and Computational Applications (MCA) is devoted to original research in the field of engineering, natural sciences or social sciences where mathematical and/or computational techniques are necessary for solving specific problems. The aim of the journal is to provide a medium by which a wide range of experience can be exchanged among researchers from diverse fields such as engineering (electrical, mechanical, civil, industrial, aeronautical, nuclear etc.), natural sciences (physics, mathematics, chemistry, biology etc.) or social sciences (administrative sciences, economics, political sciences etc.). The papers may be theoretical where mathematics is used in a nontrivial way or computational or combination of both. Each paper submitted will be reviewed and only papers of highest quality that contain original ideas and research will be published. Papers containing only experimental techniques and abstract mathematics without any sign of application are discouraged.
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