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Solving routing and spectrum allocation problems in flexgrid optical networks using pre-computing strategies

机译:使用预计算策略解决灵活光网络中的路由和频谱分配问题

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Flexible optical network architectures are considered a very promising solution where spectrum resources are allocated within flexible frequency grids. This paper presents a minimum spectrum utilization (SU) and average path length (APL) approach to solve the (off-line) routing and spectrum allocation problem (RSA) based on combining a simple ordering precomputation strategy, namely most subcarriers first (MSF) with three nature-inspired algorithms. These algorithms are ant colony optimization, differential evolution based relative position indexing ( DE- RPI), and differential evolution general combinatorial (DE-GC). We begin by showing that MSF is the most effective ordering pre-computation strategy when compared to other well-known typical heuristics in the literature, such as first-fit, and longest path first. Then, we apply MSF in combination with the three nature-inspired algorithms to simultaneously optimize the SU and APL. The usefulness of MSF ordering pre-computation strategy is presented via a comparison of results obtained when using and not using MSF under the same scenarios. The algorithms are evaluated in benchmark optical networks, such as the NSFNet, the European optical network, and the 40-node USA network. We show that DE-RPI with MSF ordering pre-computation is the best option to solve the RSA problem, obtaining an average improvement percentage in the range of 0.9772-4.4086% on the SU and from -0.1668 to 0.8511% on the APL when compared to other meta-heuristics, either with or without the MSF ordering policy.
机译:灵活的光网络架构被认为是非常有希望的解决方案,其中频谱资源在柔性频率网格中分配。本文提出了最小的频谱利用(SU)和平均路径长度(APL)方法,以解决(离线)路由和频谱分配问题(RSA),基于组合简单的订购预先计算策略,即最重要的子载波(MSF)用三种自然启发算法。这些算法是蚁群优化,基于差分演化的相对位置索引(DE-RPI)和差分演进总组合(DE-GC)。我们首先表明MSF是与文献中的其他众所周知的典型启发式相比,如第一款,首先是最长的路径的最有效的订购预算策略。然后,我们将MSF与三种自然启发算法结合使用,同时优化SU和APL。通过比较在同一方案下使用和不使用MSF时获得的结果来呈现MSF订购预计算策略的有用性。该算法在基准光网络中评估,例如NSFNET,欧洲光网络和40节点USA网络。我们显示DE-RPI与MSF订购预计算是解决RSA问题的最佳选择,在SU上的平均改善百分比为0.9772-4.4086%,与APL的-0.1668到0.8511%相比到其他元启发式,无论是在没有MSF订购策略的情况下。

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