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A Joint Power Efficient Server and Network Consolidation approach for virtualized data centers
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Computer Science. University of Naples Federico II.ORCID iD: 0000-0001-8802-504X
University of Naples Federico II.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Computer Science. (Distributed systems and communication, DISCO)ORCID iD: 0000-0002-9446-8143
2018 (English)In: Computer Networks, ISSN 1389-1286, E-ISSN 1872-7069, Vol. 130, 65-80 p.Article in journal (Refereed) Published
Abstract [en]

Cloud computing and virtualization are enabling technologies for designing energy-aware resource management mechanisms in virtualized data centers. Indeed, one of the main challenges of big data centers is to decrease the power consumption, both to cut costs and to reduce the environmental impact. To this extent, Virtual Machine (VM) consolidation is often used to smartly reallocate the VMs with the objective of reducing the power consumption, by exploiting the VM live migration. The consolidation problem consists in finding the set of migrations that allow to keep turned on the minimum number of servers needed to host all the VMs. However, most of the proposed consolidation approaches do not consider the network related consumption, which represents about 10–20% of the total energy consumed by IT equipment in real data centers. This paper proposes a novel joint server and network consolidation model that takes into account the power efficiency of both the switches forwarding the traffic and the servers hosting the VMs. It powers down switch ports and routes traffic along the most energy efficient path towards the least energy consuming server under QoS constraints. Since the model is complex, a fast Simulated Annealing based Resource Consolidation algorithm (SARC) is proposed. Our numerical results demonstrate that our approach is able to save on average 50% of the network related power consumption compared to a network unaware consolidation.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 130, 65-80 p.
Keyword [en]
Cloud, Virtualization, Power, Green computing, Simulated annealing
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-65324DOI: 10.1016/j.comnet.2017.11.003OAI: oai:DiVA.org:kau-65324DiVA: diva2:1162913
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Funder
Knowledge Foundation
Available from: 2017-12-05 Created: 2017-12-05 Last updated: 2018-01-13

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