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Erschienen in: Cluster Computing 4/2020

08.01.2020

The \(CiS^2\): a new metric for performance and energy trade-off in consolidated servers

verfasst von: Carlos Juiz, Belen Bermejo

Erschienen in: Cluster Computing | Ausgabe 4/2020

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Abstract

The increased use of cloud services has turned the virtualization in the main technology that supports cloud datacentres. To reduce the increment of power consumption caused in datacenters due to the addition of physical servers, system administrators are using virtual machine consolidation (VMC) techniques which tries to allocate the adequate number of virtual machines per physical server. Therefore, VMC increases server resources utilization and as a consequence its performance degradation and the energy consumption too. Then, a trade-off between the performance and the energy consumption exists when consolidating virtual machines. This trade-off is difficult to quantify and also to determine the servers efficiency taking into account a specific number of allocated virtual machines. Because of this, it is crucial for system administrators having a simple metric that assists the VMC making-decision process. In this paper, we propose the \(CiS^2\) index, a metric to quantify this performance-energy trade-off. Also, this index can help system administrators to decide about the servers’ efficiency through benchmarking and to select the most efficient server through a proposed algorithm. Besides, we propose a simple graphical representation of the index to distinguish graphically the efficient and non-efficient server consolidations. We validate the index in a theoretical manner and performing real experiments in different physical servers under CPU workload saturation. Obtained results show that the proposed index reflects the performance-energy trade-off behaviour and it helps systems’ administrators when consolidating virtual machines.

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Metadaten
Titel
The : a new metric for performance and energy trade-off in consolidated servers
verfasst von
Carlos Juiz
Belen Bermejo
Publikationsdatum
08.01.2020
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe 4/2020
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-019-03043-8

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