Abstract

Software-defined networks have become more common in data centers. The programmability of these networks is a great feature that allows innovation to be deployed fast, following the increasing number of new applications. This growth comes with a cost of more processing power and energy consumption. Many researchers have tackled this issue using existing routing techniques to dynamically adjust the network forwarding plane to save energy. On the control-plane, researchers have found algorithms for positioning the controller in a way to reduce the number of used links, thus reducing energy. These strategies reduce energy consumption at the expense of processing power of the controllers. This paper proposes a novel approach to energy efficiency focused on the network’s control-plane, which is complementary to the many already existing data-plane solutions. It takes advantage of the parallel processing capabilities of modern off-the-shelf multicore processors to split the many tasks of the controller among the cores. By dividing the tasks among homogeneous cores, one can lower the frequency of operations, lowering the overall energy consumption while keeping the same quality of service level. We show that a multicore controller can use an off-the-shelf multicore processor to save energy while keeping the level of service. We performed experiments based on standard network measures, namely latency and throughput, and standard energy efficiency metrics for data centers such as the Communication Network Energy Efficiency (CNEE) metric. Higher energy efficiency is achieved by a parallel implementation of the controller and lowering each core’s frequency of operation. In our experiments, we achieved a drop of 28% on processor energy use for a constant throughput scenario when comparing with the single-core approach.

Highlights

  • Data center networks are increasing in size, data processing capacity and throughput to attend to the high demand of computing services required by: the growing demand on the cloud [1], smart cities, the advent of the Internet of Things (IoT), big data applications and deep neural networks among other technologies

  • A set of experiments are presented to show the reduced energy use on multicore SDN controllers compared to their single-core counterparts

  • This study shows that an SDN controller can have an improved energy efficiency by lowering its operating frequency using the parallel nature and availability of current multicore processors

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Summary

Introduction

Data center networks are increasing in size, data processing capacity and throughput to attend to the high demand of computing services required by: the growing demand on the cloud [1], smart cities, the advent of the Internet of Things (IoT), big data applications and deep neural networks among other technologies. The demand from DC for energy and its related environmental implications are increasing . A study by Van Heddeghem et al [2] shows that the energy consumption of Information and Communication. Technology (ICT) equipment was responsible for 4.6% of all energy consumption by 2012. Masanet et al [4] showed that total energy consumption of data centers worldwide has increased from 95 TWh in 2010 to TWh in 2018, and it is expected to reach 155 TWh by 2023. The equipment present on a Data Center (DC) can be divided into three categories: infrastructure, servers and network. The energy-efficiency of a data center has been measured as the portion of overall energy consumption that is delivered to ICT equipment, 4.0/)

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