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On the Parallelization of Spectrum Defragmentation Reconfigurations in Elastic Optical Networks

机译:弹性光网络中频谱碎片整理重新配置的并行化

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Flexible-grid elastic optical networks (EONs) have attracted intensive research interests for the agile spectrum management in the optical layer. Meanwhile, due to the relatively small spectrum allocation granularity, spectrum fragmentation has been commonly recognized as one of the key factors that can deteriorate the performance of EONs. To alleviate spectrum fragmentation, various defragmentation (DF) schemes have been considered to consolidate spectrum utilization in EONs through connection reconfigurations. However, most of the previous approaches operate in the sequential manner (Seq-DF), i.e., involving a sequence of reconfigurations to progressively migrate highly fragmented spectrum utilization to consolidated state. In this paper, we propose to perform the DF operations in a parallel manner (Par-DF), i.e., conducting all the DF-related connection reconfigurations simultaneously. We first provide a detailed analysis on the latency and disruption of Seq-DF and Par-DF in EONs, and highlight the benefits of Par-DF. Then, we study two types of Par-DF approaches in EONs, i.e., reactive Par-DF (re-Par-DF) and proactive Par-DF (pro-Par-DF). We perform hardness analysis on them, and prove that the problem of re-Par-DF is NP-hard in the strong sense while pro-Par-DF is an APX -hard problem. Next, we focus on pro-Par-DF and propose a Lagrangian-relaxation (LR) based heuristic to solve it time-efficiently. The proposed algorithm decomposes the original problem into several independent subproblems and ensures that each of them can be solved efficiently. The LR based approach informs us the proximity of current feasible solution to the optimal one constantly, and offers a near-optimal performance (relative dual gap <5%) within 500 iterations in most simulations. Extensive simulations also verify that the proposed pro-Par-DF approach outperforms Seq-DF in terms of the DF Latency, Disruption and Cost.
机译:柔性网格弹性光网络(EON)已吸引了对光学层中敏捷频谱管理的广泛研究兴趣。同时,由于相对较小的频谱分配粒度,频谱碎片化已被普遍认为是可使EON性能下降的关键因素之一。为了减轻频谱碎片,已考虑使用各种碎片整理(DF)方案通过连接重新配置来巩固EON中的频谱利用率。然而,大多数先前的方法以顺序方式(Seq-DF)操作,即,涉及一系列重新配置以将高度碎片化的频谱利用逐渐迁移到合并状态。在本文中,我们建议以并行方式(Par-DF)执行DF操作,即同时进行所有与DF相关的连接重新配置。我们首先提供有关EON中Seq-DF和Par-DF的延迟和中断的详细分析,并重点介绍Par-DF的优势。然后,我们研究了EON中的两种Par-DF方法,即反应式Par-DF(re-Par-DF)和主动式Par-DF(pro-Par-DF)。我们对其进行了硬度分析,并证明了从本质上说,re-Par-DF的问题是NP-hard问题,而pro-Par-DF的问题是APX-hard问题。接下来,我们专注于pro-Par-DF并提出基于拉格朗日松弛(LR)的启发式算法,以高效地解决它。所提出的算法将原始问题分解为几个独立的子问题,并确保可以有效地解决每个子问题。基于LR的方法不断地告诉我们当前可行的解决方案与最佳解决方案的接近度,并且在大多数仿真中,在500次迭代中提供了接近最佳的性能(相对双间隙<5%)。广泛的仿真还验证了所提出的pro-Par-DF方法在DF延迟,中断和成本方面优于Seq-DF。

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