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An SDN Focused Approach for Energy Aware Traffic Engineering in Data Centers
There is a lot of effort to limit the impact of CO(2) emissions from the information communication technologies (ICT) industry by reducing the energy consumption on all aspects of networking technologies. In a service provider network, data centers (DCs) are the major power consumer and considerable...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767089/ https://www.ncbi.nlm.nih.gov/pubmed/31540115 http://dx.doi.org/10.3390/s19183980 |
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author | Charalampou, Paris Sykas, Efstathios D. |
author_facet | Charalampou, Paris Sykas, Efstathios D. |
author_sort | Charalampou, Paris |
collection | PubMed |
description | There is a lot of effort to limit the impact of CO(2) emissions from the information communication technologies (ICT) industry by reducing the energy consumption on all aspects of networking technologies. In a service provider network, data centers (DCs) are the major power consumer and considerable gains are expected by regulating the operation network devices. In this context, we developed a mixed integer programming (MIP) algorithm to optimize the power consumption of network devices via energy aware traffic engineering. We verified our approach by simulating DC network topologies and demonstrated that clear benefits can be achieved for various network sizes and traffic volumes. Our algorithm can be easily implemented as an application in the software-defined networking (SDN) paradigm, making quite feasible its deployment in a production environment. |
format | Online Article Text |
id | pubmed-6767089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-67670892019-10-02 An SDN Focused Approach for Energy Aware Traffic Engineering in Data Centers Charalampou, Paris Sykas, Efstathios D. Sensors (Basel) Article There is a lot of effort to limit the impact of CO(2) emissions from the information communication technologies (ICT) industry by reducing the energy consumption on all aspects of networking technologies. In a service provider network, data centers (DCs) are the major power consumer and considerable gains are expected by regulating the operation network devices. In this context, we developed a mixed integer programming (MIP) algorithm to optimize the power consumption of network devices via energy aware traffic engineering. We verified our approach by simulating DC network topologies and demonstrated that clear benefits can be achieved for various network sizes and traffic volumes. Our algorithm can be easily implemented as an application in the software-defined networking (SDN) paradigm, making quite feasible its deployment in a production environment. MDPI 2019-09-14 /pmc/articles/PMC6767089/ /pubmed/31540115 http://dx.doi.org/10.3390/s19183980 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Charalampou, Paris Sykas, Efstathios D. An SDN Focused Approach for Energy Aware Traffic Engineering in Data Centers |
title | An SDN Focused Approach for Energy Aware Traffic Engineering in Data Centers |
title_full | An SDN Focused Approach for Energy Aware Traffic Engineering in Data Centers |
title_fullStr | An SDN Focused Approach for Energy Aware Traffic Engineering in Data Centers |
title_full_unstemmed | An SDN Focused Approach for Energy Aware Traffic Engineering in Data Centers |
title_short | An SDN Focused Approach for Energy Aware Traffic Engineering in Data Centers |
title_sort | sdn focused approach for energy aware traffic engineering in data centers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767089/ https://www.ncbi.nlm.nih.gov/pubmed/31540115 http://dx.doi.org/10.3390/s19183980 |
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