Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/2304696.2304718acmconferencesArticle/Chapter ViewAbstractPublication PagescomparchConference Proceedingsconference-collections
research-article

Optimizing the energy consumption of large-scale applications

Published: 25 June 2012 Publication History

Abstract

The energy consumption of large IT infrastructures is becoming a major concern, since it represents one of the principal operation costs. While modern devices (e.g., processors, disks) have the capability of reducing their power consumption by running at lower speed, this feature must be used with care, as slowing down devices may increase the execution time of the applications beyond acceptable limits. In this paper we propose the qoS AWare energY managER (SAWYER), a framework for dynamically reducing the energy requirement of large-scale applications subject to response time constraints. SAWYER identifies the optimal performance/power consumption tradeoff such that the overall energy requirement is minimized and the application response time is kept below a pre-defined maximum value. This is achieved using a control loop based on a greedy optimization strategy which uses a Queueing Network performance model to quickly evaluate different power settings, ensuring that the expected system response time is kept below the threshold. SAWYER is completely transparent and does not require any modification of the application itself.

References

[1]
B. Abrahao, V. Almeida, J. Almeida, A. Zhang, D. Beyer, and F. Safai. Self-adaptive sla-driven capacity management for internet services. In Network Operations and Management Symposium, 2006. NOMS 2006. 10th IEEE/IFIP, pages 557--568, Apr. 2006.
[2]
S. Balsamo. Product form queueing networks. In G. Haring, C. Lindemann, and M. Reiser, editors, Performance Evaluation: Origins and Directions, volume 1769 of Lecture Notes in Computer Science, pages 377--401. Springer Berlin/Heidelberg, 2000.
[3]
D. Barbagallo, E. Di Nitto, D. J. Dubois, and R. Mirandola. A bio-inspired algorithm for energy optimization in a self-organizing data center. In Proceedings of the First international conference on Self-organizing architectures, SOAR'09, pages 127--151, Berlin, Heidelberg, 2010. Springer-Verlag.
[4]
L. A. Barroso and U. Hölzle. The case for energy-proportional computing. Computer, 40(12):33--37, 2007.
[5]
R. F. Berry. Trends, challenges and opportunities for performance engineering with modern business software. IEE Proceedings - Software, 150(4):223--229, 2003.
[6]
L. Bertini, J. C. Leite, and D. Mossé. Power optimization for dynamic configuration in heterogeneous web server clusters. Journal of Systems and Software, 83(4):585 -- 598, 2010.
[7]
R. Calinescu and M. Z. Kwiatkowska. Using quantitative analysis to implement autonomic it systems. In ICSE, pages 100--110. IEEE, 2009.
[8]
J. B. Carter and K. Rajamani. Designing energy-efficient servers and data centers. IEEE Computer, 43(7):76--78, 2010.
[9]
Y. Chen, A. Das, W. Qin, A. Sivasubramaniam, Q. Wang, and N. Gautam. Managing server energy and operational costs in hosting centers. SIGMETRICS Perform. Eval. Rev., 33(1):303--314, 2005.
[10]
B. H. C. Cheng, R. de Lemos, H. Giese, P. Inverardi, and J. Magee, editors. Software Engineering for Self-Adaptive Systems {outcome of a Dagstuhl Seminar}, volume 5525 of Lecture Notes in Computer Science. Springer, 2009.
[11]
I. Cunha, I. Viana, J. Palotti, J. Almeida, and V. Almeida. Analyzing security and energy tradeoffs in autonomic capacity management. In Network Operations and Management Symposium (NDMS 2008). IEEE, pages 302--309, Apr. 2008.
[12]
E. di Nitto, D. J. Dubois, and R. Mirandola. On exploiting decentralized bio-inspired self-organization algorithms to develop real systems. In Proceedings of the 2009 ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems, pages 68--75, Washington, DC, USA, 2009. IEEE Computer Society.
[13]
J. W. Eaton. GNU Octave Manual. Network Theory Limited, 2002.
[14]
E. N. Elnozahy, M. Kistler, and R. Rajamony. Energy conservation policies for web servers. In USENIX Symposium on Internet Technologies and Systems, 2003.
[15]
H. Feng, Z. Liu, C. H. Xia, and L. Zhang. Load shedding and distributed resource control of stream processing networks. Perf. Eval., 64:1102--1120, October 2007.
[16]
Hewlett-Packard Corporation, Intel Corporation, Microsoft Corporation, Phoenix Technologies Ltd., and Toshiba Corporation. Advanced configuration and power interface specification, Dec. 6 2011. Revision 5.0, Available at http://www.acpi.info/.
[17]
M. C. Huebscher and J. A. McCann. A survey of autonomic computing--degrees, models, and applications. ACM Comput. Surv., 40(3), 2008.
[18]
J. O. Kephart and D. M. Chess. The vision of autonomic computing. IEEE Computer, 36(1):41--50, 2003.
[19]
P. Kogge. The tops in flops. IEEE Spectrum, 48:48--54, Jan. 2011.
[20]
J. G. Koomey. Estimating Total Power Consumption by Servers in the U.S. and the World. Final report, Feb. 5 2007. Available at http://sites.amd.com/de/Documents/svrpwrusecompletefinal.pdf.
[21]
A. Krioukov, P. Mohan, S. Alspaugh, L. Keys, D. Culler, and R. Katz. Napsac: design and implementation of a power-proportional web cluster. SIGCOMM Comput. Commun. Rev., 41:102--108.
[22]
E. D. Lazowska, J. Zahorjan, G. S. Graham, and K. C. Sevcik. Quantitative System Performance: Computer System Analysis Using Queueig Network Models. Prentice-Hall, 1984.
[23]
J. D. C. Little. A proof for the queuing formula: L=łambda W. Operations Research, 9(3):383--387, 1961.
[24]
Y. Liu and H. Zhu. A survey of the research on power management techniques for high-performance systems. Software: Practice and Experience, 40(11):943--964, 2010.
[25]
J. Lüthi and G. Haring. Mean value analysis for queueing network models with intervals as input parameters. Perf. Eval., 32(3):185--215, 1998.
[26]
M. Marzolla, O. Babaoglu, and F. Panzieri. Server consolidation in clouds through gossiping. In Int. Symp. World of Wireless, Mobile and Multimedia Networks (WoWMoM), pages 1--6, June 20--24 2011.
[27]
D. Meisner, B. T. Gold, and T. F. Wenisch. Powernap: eliminating server idle power. SIGPLAN Not., 44(3):205--216, Mar. 2009.
[28]
D. Meisner, C. M. Sadler, L. A. Barroso, W.-D. Weber, and T. F. Wenisch. Power management of online data-intensive services. SIGARCH Comput. Archit. News, 39(3):319--330, June 2011.
[29]
J. M. Rabaey, A. Chandrakasan, and B. Nikolic. Digital Integrated Circuits--A Design Perspective. Prentice Hall, 2003. 2nd Edition.
[30]
P. Ranganathan. Recipe for efficiency: principles of power-aware computing. Comm. ACM, 53(4):60--67, 2010.
[31]
M. Reiser and S. S. Lavenberg. Mean-value analysis of closed multichain queuing networks. J. ACM, 27:313--322, April 1980.
[32]
B. Urgaonkar, G. Pacifici, P. Shenoy, M. Spreitzer, and A. Tantawi. Analytic modeling of multitier internet applications. ACM Trans. Web, 1, May 2007.
[33]
B. Urgaonkar, P. Shenoy, A. Chandra, P. Goyal, and T. Wood. Agile dynamic provisioning of multi-tier internet applications. ACM Trans. Auton. Adapt. Syst., 3(1):1--39, 2008.
[34]
J. Zahorjan, K. C. Sevcick, D. L. Eager, and B. I. Galler. Balanced job bound analysis of queueing networks. Comm. ACM, 25(2):134--141, Feb. 1982.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
QoSA '12: Proceedings of the 8th international ACM SIGSOFT conference on Quality of Software Architectures
June 2012
164 pages
ISBN:9781450313469
DOI:10.1145/2304696
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 June 2012

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. green computing
  2. qos management

Qualifiers

  • Research-article

Conference

Comparch '12
Sponsor:

Acceptance Rates

Overall Acceptance Rate 46 of 131 submissions, 35%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 219
    Total Downloads
  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)0
Reflects downloads up to 27 Jan 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media