对抗光网络资源紧张:需求响应动态OSNR余量分配

R. B. Lourenço, M. Tornatore, B. Mukherjee
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引用次数: 0

摘要

一些网络运营商以高平均利用率运行他们的网络。在高利用率的情况下,由于没有足够的容量来服务所有提供的流量,更有可能发生资源紧缩。一种解决方案是通过能够动态调整调制的转发器使用更高的调制格式(提供更高的吞吐量)来增加底层光网络的容量。这是可能的,因为运营商传统上使用较大的光信噪比(OSNR)余量(即某种调制的最小OSNR与观测到的OSNR之间的差值)。使用具有更高频谱效率的调制格式(即增加调制)会降低OSNR余量。当OSNR边际较小时,OSNR波动可能会触发应答器使用更稳健、更低的调制。如果这些变化频繁,服务质量可能会受到影响。为了减少调制变化的数量,我们提出了一个机器学习模型来预测OSNR。当资源紧缩开始时,我们选择在每个光路中使用什么调制(根据预测);当这一阶段结束后,我们将以需求响应的方式恢复到高利润率。我们的结果表明,在资源紧缩期间,与使用保守OSNR裕度的情况相比,我们的方法承载了更大的负载,而与始终使用最严格的OSNR裕度的系统相比,产生的调制变化要少得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combating Resource Crunch in an Optical Network: Demand-Responsive Dynamic OSNR Margin Allocation
Several network operators run their networks at high average utilization. At high utilization, it is more likely that Resource Crunch will occur due to there not being enough capacity to serve all offered traffic. One solution is to increase the capacity of the underlying optical network by using higher modulation formats (which provide higher throughput) through transponders capable of dynamically adjusting modulations. This is possible since operators traditionally use large Optical Signal-to-Noise Ratio (OSNR) margins (i.e., the difference between the minimum OSNR for a certain modulation and the observed OSNR). Using modulation formats with higher spectral efficiency (i.e., increasing modulation) decreases OSNR margins. When OSNR margins are small, OSNR fluctuations may trigger the transponder to use more robust, lower modulations. If these changes are frequent, Quality of Service may suffer. To reduce the number of modulation changes, we propose a Machine Learning model to forecast OSNR. When Resource Crunch starts, we choose what modulations to use in each lightpath (according to the forecast); and, when it is over, we revert to large margins, in a demand-responsive manner. Our results show that, during Resource Crunch, our method carries a larger load when compared to a scenario where conservative OSNR margins are used, while incurring significantly fewer modulation changes than a system that always uses the tightest OSNR margin possible.
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