skip to main content
10.1145/1657120.1657121acmotherconferencesArticle/Chapter ViewAbstractPublication PagesmiddlewareConference Proceedingsconference-collections
research-article

Power-aware provisioning of Cloud resources for real-time services

Published:30 November 2009Publication History

ABSTRACT

Reducing energy consumption has been an essential technique for Cloud resources or datacenters, not only for operational cost, but also for system reliability. As Cloud computing becomes emergent for Anything as a Service (XaaS) paradigm, modern real-time Cloud services are also available throughout Cloud computing. In this work, we investigate power-aware provisioning of virtual machines for real-time services. Our approach is (i) to model a real-time service as a real-time virtual machine request; and (ii) to provision virtual machines of datacenters using DVFS (Dynamic Voltage Frequency Scaling) schemes. We propose several schemes to reduce power consumption and show their performance throughout simulation results.

References

  1. N. D. Adiga, et al. An overview of the BlueGene/L supercomputer. In Proc. of ACM/IEEE Conf. on Supercomputing. Baltimore, USA, November 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Amazon Elastic Compute Cloud (Amazon EC2). http://aws.amazon.com/ec2.Google ScholarGoogle Scholar
  3. M. Armbrust, et al. Above the Clouds: A Berkeley view of cloud computing. Tech. Report No. UCB/EECS-2009-28, University of California at Berkeley, USA, February 2009.Google ScholarGoogle Scholar
  4. T. D. Burd and R. W. Brodersen. Energy efficient cmos microprocessor design. In Proc. of Annual Hawaii Intl. Conf. on System Sciences, pages 288--297, January 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. R. Buyya, R. Ranjan, and R. N. Calheiros. Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities. In Proc. of the 7th High Performance Computing and Simulation (HPCS 2009). Leipzig, Germany, June 2009.Google ScholarGoogle ScholarCross RefCross Ref
  6. M. Cardosa, M. R. Korupolu, and A. Singh. Shares and utilities based power consolidation in virtualized server environments. In Proc. of IFIP/IEEE Intl. Symp. on Integrated Network Management. USA, June 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. J. S. Chase, et al. Managing energy and server resources in hosting centers. In Proc. of 8th ACM Symp. on Operating Systems Principles. Banff, Canada, October 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. X. A. Feng and A. K. Mok. A model of hierarchical real-time virtual resources. In Proc. of 23rd IEEE Real-Time Systems Symposium. Austin, USA, Dec. 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. A. Gandhi, M. Harchol-Balter, R. Das, and C. Lefurgy. Optimal power allocation in server farms. In Proc. of Intl. Joint Conf. on Measurement and Modeling of Computer Systems, pages 157--168. Seattle, USA, June 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. R. Ge, X. Feng, and K. W. Cameron. Performance-constrained distributed DVS scheduling for scientific applications on power-aware clusters. In Proc. of ACM/IEEE Conf. on Supercomputing. Seattle, USA, November 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. C. Hsu and W. Feng. A power-aware run-time system for high-performance computing. In Proc. of ACM/IEEE Conf. on Supercomputing. Seattle, USA, November 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. N. Kappiah, V. W. Freeh, and D. K. Lowenthal. Just in time dynamic voltage scaling: Exploiting inter-node slack to save energy in MPI programs. In Proc. of ACM/IEEE Conf. on Supercomputing. Seattle, USA, November 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. K. H. Kim, R. Buyya, and J. Kim. Power aware scheduling of bag-of-tasks applications with deadline constraints on DVS-enabled clusters. In Proc. of 7th IEEE Intl. Symp. on Cluster Computing and the Grid (CCGrid'07), pages 541--548. Rio de Janeiro, Brazil, May 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. D. Kusic, et al. Power and performance management of virtualized computing environments via lookahead control. In Proc. of 5th IEEE Intl. Conf. on Autonomic Computing (ICAC 2008), pages 3--12. Chicago, USA, June 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. J. Markoff and S. Lohr. Intel's huge bet turns iffy. New York Times Technology Section, September 2002.Google ScholarGoogle Scholar
  16. L. Niu and G. Quan. Reducing both dynamic and leakage energy consumption for hard real-time systems. In Proc. of CASES'04. Washington, DC, USA, Sept. 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. D. Ongaro, A. Cox, and S. Rixner. Scheduling i/o in virtual machine monitors. In Proc. of ACM SIGPLAN/SIGOPS Intl. Conf. on Virtual Execution Environments, pages 1--10. Seattle, USA, March 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. C. Rusu, A. Ferreira, C. Scordino, A. Watson, R. Melhem, and D. Mosse. Energy-efficient real-time heterogeneous server clusters. In Proc. of the 12th IEEE Real-Time and Embedded Technology and Applications Symposium, pages 418--428. San Jose, USA, April 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. P. Scheihing. Creating energy efficient data centers. In Data Center Facilities and Engineering Conference. Washington, DC, USA, May 2007.Google ScholarGoogle Scholar
  20. I. Shin and I. Lee. Compositional real-time scheduling framework with periodic model. ACM Transactions on Embedded Computing Systems, 7(3), April 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. S. W. Son, et al. Integrated link/cpu voltage scaling for reducing energy consumption of parallel sparse matrix applications. In Proc. of 20th IEEE Intl. Parallel and Distributed Processing Symposium. Greece, April 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. S. Srikantaiah, A. Kansal, and F. Zhao. Energy aware consolidation for cloud computing. In Workshop on Power Aware Computing and Systems (HotPower '08). San Diego, USA, December 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. A. Verma, P. Ahuja, and A. Neogi. pMapper: Power and migration cost aware application placement in virtualized systems. In Proc. of 9th ACM/IFIP/USENIX Intl. Conf. on Middleware. Leuven, Belgium, December 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. A. Verma, P. Ahuja, and A. Neogi. Power-aware dynamic placement of HPC applications. In Proc. of ICS'08, pages 175--184. Agean Sea, Greece, June 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. VirtualLogicx Real-Time Virutulalization and VLX. VirtualLogix, http://www.osware.com.Google ScholarGoogle Scholar
  26. L. Wang and Y. Lu. Efficient power management of heterogeneous soft real-time clusters. In Proc. of IEEE Real-Time Systems Sym. Barcelona, Spain, Dec. 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. W. Warren, E. Weigle, and W. Feng. High-density computing: A 240-node Beowulf in one cubic meter. In Proc. of ACM/IEEE Conf. on Supercomputing. Baltimore, USA, November 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. S. Yoo, M. Park, and C. Yoo. A step to support real-time in a virtual machine monitor. In Proc. of 6th IEEE Consumer Communications and Networking Conference. Las Vegas, USA, January 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Power-aware provisioning of Cloud resources for real-time services

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Other conferences
        MGC '09: Proceedings of the 7th International Workshop on Middleware for Grids, Clouds and e-Science
        November 2009
        41 pages
        ISBN:9781605588476
        DOI:10.1145/1657120

        Copyright © 2009 ACM

        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]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 30 November 2009

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        Overall Acceptance Rate14of36submissions,39%

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader