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Greening backbone networks: reducing energy consumption by shutting off cables in bundled links

Published: 30 August 2010 Publication History

Abstract

In backbone networks, the line cards that drive the links between neighboring routers consume a large amount of energy. Since these networks are typically overprovisioned, selectively shutting down links during periods of low demand seems like a good way to reduce energy consumption. However, removing entire links from the topology often reduces capacity and connectivity too much, and leads to transient disruptions in the routing protocol. In this paper, we exploit the fact that many links in core networks are actually 'bundles' of multiple physical cables and line cards that can be shut down independently. Since identifying the optimal set of cables to shut down is an NP-complete problem, we propose several heuristics based on linear optimization techniques. We evaluate our heuristics on topology and traffic data from the Abilene backbone as well as on two synthetic topologies. The energy savings are significant, our simplest heuristic reduces energy consumption by 79% on Abilene under realistic traffic loads and bundled links consisting of five cables. Our optimization techniques run efficiently using standard optimization tools, such as the AMPL/CPLEX solver, making them a practical approach for network operators to reduce the energy consumption of their backbones.

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    cover image ACM Conferences
    Green Networking '10: Proceedings of the first ACM SIGCOMM workshop on Green networking
    August 2010
    92 pages
    ISBN:9781450301961
    DOI:10.1145/1851290
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 30 August 2010

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    Author Tags

    1. energy-efficiency
    2. optimization
    3. routing
    4. traffic engineering

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    SIGCOMM '10
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    SIGCOMM '10: ACM SIGCOMM 2010 Conference
    August 30, 2010
    New Delhi, India

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    • (2024)SafeDRL: Dynamic Microservice Provisioning With Reliability and Latency Guarantees in Edge EnvironmentsIEEE Transactions on Computers10.1109/TC.2023.332919473:1(235-248)Online publication date: Jan-2024
    • (2023)Router Activation Heuristics for Energy-Saving ECMP and Valiant Routing in Data Center NetworksEnergies10.3390/en1610413616:10(4136)Online publication date: 17-May-2023
    • (2023)A Novel Dynamic Software-Defined Networking Approach to Neutralize Traffic BurstComputers10.3390/computers1207013112:7(131)Online publication date: 27-Jun-2023
    • (2023)On Modelling the Power Consumption of a Backbone Network2023 IEEE International Conference on Communications Workshops (ICC Workshops)10.1109/ICCWorkshops57953.2023.10283615(1842-1847)Online publication date: 28-May-2023
    • (2023)Controlling Air Pollution in Data Centers using Green Data Centers2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW)10.1109/CCGridW59191.2023.00043(200-205)Online publication date: May-2023
    • (2022)A Perspective on Stable Wired Networks while Reducing Energy Use with Load BalanceSoutheastCon 202210.1109/SoutheastCon48659.2022.9764132(23-30)Online publication date: 26-Mar-2022
    • (2022)ALR Switching and Routing Strategy for Multiple Sites Based on Traffic Splitting Method for Power Saving2022 Tenth International Symposium on Computing and Networking Workshops (CANDARW)10.1109/CANDARW57323.2022.00063(33-39)Online publication date: Nov-2022
    • (2022)Multi-Stage Power-Aware Intelligent Adaptive Routing Algorithms in Bundled Links Based Backbone NetworksIEEE Access10.1109/ACCESS.2022.321305710(109863-109893)Online publication date: 2022
    • (2021)An LSTM Framework for Software-Defined MeasurementIEEE Transactions on Network and Service Management10.1109/TNSM.2020.304015718:1(855-869)Online publication date: Mar-2021
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