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ALPACA: Application Performance Aware Server Power Capping
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. (Distributed Systems)ORCID-id: 0000-0001-8178-3921
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. College of Information and Computer Sciences, University of Massachusetts Amherst. (Distributed Systems)
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. (Distributed Systems)ORCID-id: 0000-0003-4113-4788
Visa övriga samt affilieringar
2018 (Engelska)Ingår i: ICAC 2018: 2018 IEEE International Conference on Autonomic Computing (ICAC), Trento, Italy, September 3-7, 2018, IEEE Computer Society, 2018, s. 41-50Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Server power capping limits the power consumption of a server to not exceed a specific power budget. This allows data center operators to reduce the peak power consumption at the cost of performance degradation of hosted applications. Previous work on server power capping rarely considers Quality-of-Service (QoS) requirements of consolidated services when enforcing the power budget. In this paper, we introduce ALPACA, a framework to reduce QoS violations and overall application performance degradation for consolidated services. ALPACA reduces unnecessary high power consumption when there is no performance gain, and divides the power among the running services in a way that reduces the overall QoS degradation when the power is scarce. We evaluate ALPACA using four applications: MediaWiki, SysBench, Sock Shop, and CloudSuite’s Web Search benchmark. Our experiments show that ALPACA reduces the operational costs of QoS penalties and electricity by up to 40% compared to a non optimized system. 

Ort, förlag, år, upplaga, sidor
IEEE Computer Society, 2018. s. 41-50
Serie
IEEE Conference Publication, ISSN 2474-0756
Nyckelord [en]
power capping, performance degradation, power-performance tradeoffs
Nationell ämneskategori
Datorsystem
Forskningsämne
administrativ databehandling
Identifikatorer
URN: urn:nbn:se:umu:diva-132428DOI: 10.1109/ICAC.2018.00014ISBN: 978-1-5386-5139-1 (tryckt)OAI: oai:DiVA.org:umu-132428DiVA, id: diva2:1081324
Konferens
15th IEEE International Conference on Autonomic Computing (ICAC 2018)
Tillgänglig från: 2017-03-13 Skapad: 2017-03-13 Senast uppdaterad: 2019-08-07Bibliografiskt granskad
Ingår i avhandling
1. Analysing, modelling and controlling power-performance tradeoffs in data center infrastructures
Öppna denna publikation i ny flik eller fönster >>Analysing, modelling and controlling power-performance tradeoffs in data center infrastructures
2017 (Engelska)Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
Alternativ titel[sv]
Analys, modellering och reglering för avvägning mellan prestanda och strömförbrukning i datacenter
Abstract [en]

The aim of this thesis is to analyse the power-performance tradeoffs in datacenter servers, create models that capture these tradeoffs, and propose controllers to optimise the use of data center infrastructures taking the tradeoffs into consideration. The main research problem that we investigate in this thesis is how to increase the power efficiency of data center servers taking into account the power-performance tradeoffs.

The main cause for this research is the massive power consumption of data centers that is a concern both from the financial and environmental footprint perspectives. Irrespectively of the approaches taken to enhance data center power efficiency, substantial reductions in the power consumption of data center servers easily lead to performance degradation of hosted applications, which causes customers dissatisfaction. Therefore, it is crucial for the data center operators to understand and control the power-performance tradeoffs.

The research methods used in this thesis include experiments on real testbeds, applying statistical methods to create power-performance models, development of various optimisation techniques to improve the energy-efficiency of servers, and simulations to evaluate proposed solutions at scale.

As a result of the research presented in this thesis, we propose taxonomies for selected aspects of data center configurations, events, management actions, and monitored metrics. We discuss the relationships between these elements and to support the analysis present results from a set of testbed experiments.We show limitations in the applicability of various data center management actions, including Dynamic Voltage Frequency Scaling (DVFS), Running Average Power Limit (RAPL), CPU Pinning, horizontal and vertical scaling. Finally, we propose a power budgeting controller that minimizes the performance degradation while enforcing the power limits.

The outcomes of this thesis can be used by the data center operators to improve the energy-efficiency of servers and reduce the overall power consumption with minimized performance degradation. Moreover, the software artifacts including virtual machine images, scripts, and simulator are available online.

Future work includes further investigation of the problem of graceful performance degradation under power limits, incorporating multi-layer applications spread among several servers and load balancing controller.

Ort, förlag, år, upplaga, sidor
Umeå: Umeå University, 2017
Serie
Report / UMINF, ISSN 0348-0542 ; 17.04
Nationell ämneskategori
Datorsystem
Identifikatorer
urn:nbn:se:umu:diva-132430 (URN)978-91-7601-683-1 (ISBN)
Presentation
2017-03-28, N360, Naturvetarhuset, Universitetsvägen, Umeå, 13:15 (Engelska)
Handledare
Tillgänglig från: 2017-04-13 Skapad: 2017-03-13 Senast uppdaterad: 2018-06-09Bibliografiskt granskad
2. May the power be with you: managing power-performance tradeoffs in cloud data centers
Öppna denna publikation i ny flik eller fönster >>May the power be with you: managing power-performance tradeoffs in cloud data centers
2019 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Alternativ titel[sv]
Må kraften vara med dig : dynamisk avvägning mellan prestanda och strömförbrukning i datacenter
Abstract [en]

The overall goal of the work presented in this thesis was to find ways of managing power-performance tradeoffs in cloud data centers. To this end, the relationships between the power consumption of data center servers and the performance of applications hosted in data centers are analyzed, models that capture these relationships are developed, and controllers to optimize the use of data center infrastructures are proposed.

The studies were motivated by the massive power consumption of modern data centers, which is a matter of significant financial and environmental concern. Various strategies for improving the power efficiency of data centers have been proposed, including server consolidation, server throttling, and power budgeting. However, no matter what strategy is used to enhance data center power efficiency, substantial reductions in the power consumption of data center servers can easily degrade the performance of hosted applications, causing customer dissatisfaction. It is therefore crucial for data center operators to understand and control power-performance tradeoffs.

The research methods used in this work include experiments on real testbeds, the application of statistical methods to create power-performance models, development of various optimization techniques to improve the power efficiency of servers, and simulations to evaluate the proposed solutions at scale.

This thesis makes multiple contributions. First, it introduces taxonomies for various aspects of data center configuration, events, management actions, and monitored metrics. We discuss the relationships between these elements and support our analysis with results from a set of testbed experiments. We demonstrate limitations on the usefulness of various data center management actions for controlling power consumption, including Dynamic Voltage Frequency Scaling (DVFS) and Running Average Power Limit (RAPL). We also demonstrate similar limitations on common measures for controlling application performance, including variation of operating system scheduling parameters, CPU pinning, and horizontal and vertical scaling. Finally, we propose a set of power budgeting controllers that act at the application, server, and cluster levels to minimize performance degradation while enforcing power limits.

The results and analysis presented in this thesis can be used by data center operators to improve the power-efficiency of servers and reduce overall operational costs while minimizing performance degradation. All of the software generated during this work, including controller source code, virtual machine images, scripts, and simulators, has been open-sourced.

Ort, förlag, år, upplaga, sidor
Umeå University, 2019. s. 63
Serie
Report / UMINF, ISSN 0348-0542 ; 19.04
Nyckelord
cloud computing, data centers, power efficiency, power budgeting, application performance
Nationell ämneskategori
Datorsystem
Identifikatorer
urn:nbn:se:umu:diva-161363 (URN)978-91-7855-080-7 (ISBN)
Disputation
2019-09-06, Aula Anatomica (Bio.A.206), Biologihuset, Umeå, 13:15 (Engelska)
Opponent
Handledare
Tillgänglig från: 2019-08-15 Skapad: 2019-07-02 Senast uppdaterad: 2019-08-21Bibliografiskt granskad

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Krzywda, JakubAli-Eldin, A.Wadbro, EddieÖstberg, Per-OlovElmroth, Erik

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