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为提高能效和限制延迟匹配 SDN 和传统网络硬件。

Matching SDN and Legacy Networking Hardware for Energy Efficiency and Bounded Delay.

机构信息

atlanTTic Research Center, University of Vigo, 36310 Vigo, Spain.

出版信息

Sensors (Basel). 2018 Nov 13;18(11):3915. doi: 10.3390/s18113915.

Abstract

Both economic and environmental costs are driving much research in the area of the energy efficiency of networking equipment. This research has produced a great amount of proposals. However, the majority of them remain unimplemented due to the lack of flexibility of current hardware devices and a certain lack of enthusiasm from commercial vendors. At the same time, Software-Defined Networking (SDN) has allowed customers to control switching decisions with a flexibility and precision previously unheard of. This paper explores the potential convergence between the two aforementioned trends and presents a promising power saving algorithm that can be implemented using standard SDN capabilities of current switches, reducing operation costs on both data centers and wired access networks. In particular, we focus on minimizing the energy consumption in bundles of energy-efficient Ethernet links leveraging SDN. For this, we build on an existing theoretical algorithm and adapt it for implementing with an SDN solution. We study several approaches and compare the resulting algorithms not only according to their energy efficiency, but also taking into account additional QoS metrics. The results show that the resulting algorithm is able to closely match the theoretical results, even when taking into account the requirements of delay-sensitive traffic.

摘要

经济和环境成本都在推动网络设备能源效率领域的大量研究。这项研究产生了大量的提案。然而,由于当前硬件设备缺乏灵活性以及商业供应商缺乏一定的积极性,大多数提案仍未实施。与此同时,软件定义网络(SDN)允许客户以以前闻所未闻的灵活性和精度来控制交换决策。本文探讨了这两个上述趋势的潜在融合,并提出了一种有前途的节能算法,该算法可以利用当前交换机的标准 SDN 功能来实现,从而降低数据中心和有线接入网络的运营成本。特别是,我们专注于通过 SDN 最大化节能以太网链路束的能量消耗。为此,我们基于现有的理论算法并对其进行了调整,以便使用 SDN 解决方案进行实施。我们研究了几种方法,并根据它们的节能效率,以及考虑到其他 QoS 指标来比较所得到的算法。结果表明,即使考虑到延迟敏感型流量的要求,所得到的算法也能够很好地匹配理论结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff01/6263874/c02697cf3162/sensors-18-03915-g001.jpg

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