Revenue Maximization Leveraging Elastic Service Provisioning in Flexible Optical Networks

Cao Chen, Fen Zhou, S. Xiao
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Abstract

In presence of a high traffic load, not all offered traffic can be satisfied at all time. Luckily, several kinds of services (e.g. video, file transfer) are elastic because they can be degraded and accepted with a lower bit-rate, corresponding to a lower quality of service (QoS) level. In this paper, we aim at maximizing network revenue leveraging elastic service provisioning. To tackle this problem, we propose an integer linear programming model as well as a decomposition method, which selects a QoS level and provisions a lightpath for elastic request. Meanwhile, in order to exploit the spectrum resources of elastic services under a progressive network load, we propose an auto-degrading provisioning scheme to trigger the network reconfiguration for existing lightpaths in an effort to increase the total network revenue. Simulation results validate the revenue improvement by supporting elastic service provisioning scheme in the scenarios of static and progressive network load.
在灵活光网络中利用弹性业务发放实现收益最大化
在存在高流量负载的情况下,并非所有提供的流量都能在任何时候得到满足。幸运的是,有几种服务(如视频、文件传输)是弹性的,因为它们可以降级并接受较低的比特率,这对应于较低的服务质量(QoS)水平。在本文中,我们的目标是利用弹性服务提供最大化网络收益。为了解决这个问题,我们提出了一个整数线性规划模型和一种分解方法,该方法选择QoS级别并为弹性请求提供光路。同时,为了在渐进式网络负载下充分利用弹性业务的频谱资源,我们提出了一种自动降级供应方案,以触发现有光路的网络重构,从而提高网络总收入。仿真结果验证了在静态和渐进式网络负载场景下,支持弹性业务发放方案对收益的提高。
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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