On the energy cost of robustness for green virtual network function placement in 5G virtualized infrastructures
Next generation 5G networks will rely on virtualized Data Centers (vDC) to host virtualized network functions on commodity servers. Such Network Function Virtualization (NFV) will lead to significant savings in terms of infrastructure cost and reduced management complexity. However, green strategies...
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| Vydáno v: | Computer networks (Amsterdam, Netherlands : 1999) Ročník 125; s. 64 - 75 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article Publikace |
| Jazyk: | angličtina |
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Amsterdam
Elsevier B.V
09.10.2017
Elsevier Sequoia S.A Elsevier |
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| ISSN: | 1389-1286, 1872-7069, 1872-7069 |
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| Abstract | Next generation 5G networks will rely on virtualized Data Centers (vDC) to host virtualized network functions on commodity servers. Such Network Function Virtualization (NFV) will lead to significant savings in terms of infrastructure cost and reduced management complexity. However, green strategies for networking and computing inside data centers, such as server consolidation or energy aware routing, should not negatively impact the quality and service level agreements expected from network operators. In this paper, we study how robust strategies that place virtual network functions (VNF) inside vDC impact the energy savings and the protection level against resource demand uncertainty. We propose novel optimization models that allow the minimization of the energy of the computing and network infrastructure which is hosting a set of service chains that implement the VNFs. The model explicitly provides for robustness to unknown or imprecisely formulated resource demand variations, powers down unused routers, switch ports and servers, and calculates the energy optimal VNF placement and network embedding also considering latency constraints on the service chains. We propose both exact and heuristic methods. Our experiments were carried out using the virtualized Evolved Packet Core (vEPC), which allows us to quantitatively assess the trade-off between energy cost, robustness and the protection level of the solutions against demand uncertainty. Our heuristic is able to converge to a good solution in a very short time, in comparison to the exact solver, which is not able to output better results in a longer run as demonstrated by our numerical evaluation. We also study the degree of robustness of a solution for a given protection level and the cost of additional energy needed because of the usage of more computing and network elements. |
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| AbstractList | Next generation 5G networks will rely on virtualized Data Centers (vDC) to host virtualized network functions on commodity servers. Such Network Function Virtualization (NFV) will lead to significant savings in terms of infrastructure cost and reduced management complexity. However, green strategies for networking and computing inside data centers, such as server consolidation or energy aware routing, should not negatively impact the quality and service level agreements expected from network operators. In this paper, we study how robust strategies that place virtual network functions (VNF) inside vDC impact the energy savings and the protection level against resource demand uncertainty. We propose novel optimization models that allow the minimization of the energy of the computing and network infrastructure which is hosting a set of service chains that implement the VNFs. The model explicitly provides for robustness to unknown or imprecisely formulated resource demand variations, powers down unused routers, switch ports and servers, and calculates the energy optimal VNF placement and network embedding also considering latency constraints on the service chains. We propose both exact and heuristic methods. Our experiments were carried out using the virtualized Evolved Packet Core (vEPC), which allows us to quantitatively assess the trade-off between energy cost, robustness and the protection level of the solutions against demand uncertainty. Our heuristic is able to converge to a good solution in a very short time, in comparison to the exact solver, which is not able to output better results in a longer run as demonstrated by our numerical evaluation. We also study the degree of robustness of a solution for a given protection level and the cost of additional energy needed because of the usage of more computing and network elements. Next generation 5G networks will rely on virtualized Data Centers (vDC) to host virtualized network functions on commodity servers. Such Network Function Virtualization (NFV) will lead to significant savings in terms of infrastructure cost and reduced management complexity. However, green strategies for networking and computing inside data centers, such as server consolidation or energy aware routing, should not negatively impact the quality and service level agreements expected from network operators. In this paper, we study how robust strategies that place virtual network func- tions (VNF) inside vDC impact the energy savings and the protection level against resource demand uncertainty. We propose novel optimization mod- els that allow the minimization of the energy of the computing and network infrastructure which is hosting a set of service chains that implement the VNFs. The model explicitly provides for robustness to unknown or impre- cisely formulated resource demand variations, powers down unused routers, switch ports and servers, and calculates the energy optimal VNF placement and network embedding also considering latency constraints on the service chains. We propose both exact and heuristic methods. Our experiments were carried out using the virtualized Evolved Packet Core (vEPC), which allows us to quantitatively assess the trade-off between energy cost, robust- ness and the protection level of the solutions against demand uncertainty. Our heuristic is able to converge to a good solution in a very short time, in comparison to the exact solver, which is not able to output better results in a longer run as demonstrated by our numerical evaluation. We also study the degree of robustness of a solution for a given protection level and the cost of additional energy needed because of the usage of more computing and network elements. Peer Reviewed |
| Author | Zola, Enrica D’Andreagiovanni, Fabio Kassler, Andreas Marotta, Antonio |
| Author_xml | – sequence: 1 givenname: Antonio surname: Marotta fullname: Marotta, Antonio email: antonio.marotta@live.it, d.andreagiovann@hds.utc.fr, andreas.kassler@kau.se, enrica@entel.upc.edu organization: Karlstad University, Universitetsgatan 2, Karlstad, 65188, Sweden – sequence: 2 givenname: Fabio surname: D’Andreagiovanni fullname: D’Andreagiovanni, Fabio organization: Sorbonne Universités, Université de Technologie de Compiègne, CNRS, Heudiasyc UMR 7253, CS 60319, Compiègne 60203, France – sequence: 3 givenname: Andreas surname: Kassler fullname: Kassler, Andreas organization: Karlstad University, Universitetsgatan 2, Karlstad, 65188, Sweden – sequence: 4 givenname: Enrica surname: Zola fullname: Zola, Enrica organization: Universitat Politècnica de Catalunya, C. Jordi Girona, 1–3, Barcelona 08034, Spain |
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| Cites_doi | 10.1109/MCOM.2015.7355586 10.1016/j.asoc.2014.10.016 10.1515/9781400831050 10.1109/MCOM.2014.6736760 10.1016/j.future.2015.02.010 10.1287/opre.1030.0065 |
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| Contributor | Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica Universitat Politècnica de Catalunya. GRXCA - Grup de Recerca en Xarxes de Comunicacions Cel·lulars i Ad-hoc |
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| Copyright | 2017 Elsevier B.V. Copyright Elsevier Sequoia S.A. Oct 9, 2017 Attribution-NonCommercial-NoDerivs 3.0 Spain info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-nd/3.0/es Distributed under a Creative Commons Attribution 4.0 International License |
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| Keywords | EPC 5G Binary linear programming Robust optimization Virtualization Network function virtualization (NFV) |
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| SubjectTerms | 5G mobile communication Binary Linear Programming Chains Cloud computing Computació en núvol Computer centers Computer networks Computer Science Computing costs Comunicacions òptiques Consolidation Cost control Costs Data centers Datavetenskap Demand Energy Energy conservation Engineering Sciences EPC Experiments Heuristic Heuristic methods Infrastructure Latency Mathematical models Mathematics Minimization Network function virtualization (NFV) Networking Networks Numerical analysis Operations Research Operators Operators (mathematics) Optical communications Optimization Optimization and Control Ordinadors, Xarxes d Placement Ports Protection Robust Optimization Robustness Robustness (mathematics) Routers Savings Servers Switching theory Telecomunicació Uncertainty Virtual networks Virtualization Xarxes |
| Title | On the energy cost of robustness for green virtual network function placement in 5G virtualized infrastructures |
| URI | https://dx.doi.org/10.1016/j.comnet.2017.04.045 https://www.proquest.com/docview/1966856911 https://recercat.cat/handle/2072/293207 https://inria.hal.science/hal-01665875 https://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-64563 |
| Volume | 125 |
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