Advertisement

Service Centric Computing - Next Generation Internet Computing

  • Jerry Rolia
  • Rich Friedrich
  • Chandrakant Patel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2459)

Abstract

In the not-too-distant future, billions of people, places and things could all be connected to each other and to useful services through the Internet. In this world scalable, cost-effective information technology capabilities will need to be provisioned as service, delivered as a service, metered and managed as a service, and purchased as a service. We refer to this world as service centric computing. Consequently, processing and storage will be accessible via utilities where customers pay for what they need when they need it and where they need it. This tutorial introduces concepts of service centric computing and its relationship to the Grid. It explains a programmable data center paradigm as a flexible architecture that helps to achieve service centric computing. Case study results illustrate performance and thermal issues. Finally, key open research questions pertaining to service centric computing and Internet computing are summarized.

Keywords

Simple Object Access Protocol Open Grid Service Architecture Server Consolidation Resource Scheduler Ubiquitous Computing Application 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 8.
    Czajkowski K., Foster I., Karonis N., Kesselman C., Martin S., Smith W., and Tuecke S.: A Resource Management Architecture for Metacomputing Systems. JSSPP, 1988, 62–82.Google Scholar
  2. 9.
    Foster I., Kesselman C., Nick J., and Tuecke S.: The Physiology of the Grid: An Open Grid Services Architecture for Distributed Systems Integration. http://www.globus.org, January, 2002.
  3. 10.
    The Grid: Blueprint for a New Computing Infrastructure, Edited by Ian Foster and Carl Kesselman, July 1998, ISBN 1-55860-475-8.Google Scholar
  4. 11.
    Krauter K., Buyya R., and Maheswaran M.: A taxonomy and survey of grid resource management systems for distributed computing. Software-Practice and Experience, vol. 32, no. 2, 2002, 135–164.zbMATHCrossRefGoogle Scholar
  5. 12.
    Zhou S.: LSF: Load sharing in large-scale heterogeneous distributed systems, Workshop on Cluster Computing, 1992.Google Scholar
  6. 13.
    Litzkow M., Livny M. and Mutka M.: Condor-A Hunter of IdleWorkstations. Proceedings of the 8th International Conference on Distributed Computing Systems, June, 1998, 104–111.Google Scholar
  7. 14.
    Natrajan A., Humphrey M., and Grimshaw A.: Grids: Harnessing Geographically-Separated Resources in a Multi-Organisational Context. Proceedings of High Performance Computing Systems, June, 2001.Google Scholar
  8. 15.
    Rolia J., Singhal S. and Friedrich R.: Adaptive Internet Data Centers. Proceedings of the European Computer and eBusiness Conference (SSGRR), L’Aquila, Italy, July 2000, Italy, http://www.ssgrr.it/en/ssgrr2000/papers/053.pdf.
  9. 24.
    Appleby K., Fakhouri S., Fong L., Goldszmidt G. and Kalantar M.: Oceano-SLA Based Management of a Computing Utility. Proceedings of the IFIP/IEEE International Symposium on Integrated Network Management, May 2001.Google Scholar
  10. 25.
    Ranjan S., Rolia J., Zu H., and Knightly E.: QoS-Driven Server Migration for Internet Data Centers. Proceedings of IWQoS 2002, May 2002, 3–12.Google Scholar
  11. 26.
    Rolia J., Zhu X., Arlitt M., and Andrzejak A.: Statistical Service Assurances for Applications in Utility Grid Environments. HPL Technical Report, HPL-2002-155.Google Scholar
  12. 27.
    Anderson E., Hobbs M., Keeton K., Spence S., Uysal M., and Veitch A.: Hippodrome: running circles around storage administration. Conference on File and Storage Technologies (FAST3902), 17545188–284530 January 2002, Monterey, CA. (USENIX, Berkeley, CA.).Google Scholar
  13. 28.
    Borowsky E., Golding R., Jacobson P., Merchant A., Schreier L., Spasojevic M., and Wilkes J.: Capacity planning with phased workloads, WOSP, 1998, 199–207.Google Scholar
  14. 29.
    Foster I., Kesselman C., Lee C., Lindell R., Nahrstedt K., and Roy A.: A Distributed Resource Management Architecture that Supports Advance Reservations and Co-Allocation. Proceedings of the International Workshop on Quality of Service, 1999.Google Scholar
  15. 30.
    Andrzejak, A., Graupner, S., Kotov, V., and Trinks, H.: Self-Organizing Control in Planetary-Scale Computing. IEEE International Symposium on Cluster Computing and the Grid (CCGrid), 2nd Workshop on Agent-based Cluster and Grid Computing (ACGC), May 21–24, 2002, Berlin.Google Scholar
  16. 31.
    Patel C., Bash C., Belady C., Stahl L., and Sullivan D.: Computational Fluid Dynamics Modeling of High Compute Density Data Centers to Assure System Inlet Air Specifications. Proceedings of IPACK’01 The Pacific Rim/ASME International Electronic Packaging Technical Conference and Exhibition July 8–13, 2001, Kauai, Hawaii, USA.Google Scholar
  17. 32.
    Patel, C.D., Sharma, R.K, Bash, C.E., Beitelmal, A: Thermal Considerations in Cooling Large Scale High Compute Density Data Centers, ITherm 2002-Eighth Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems. May 2002, San Diego, California.Google Scholar
  18. 33.
    Sharma, R.K, Bash. C.E., Patel, C.D.: Dimensionless Parameters for Evaluation of Thermal Design and Performance of Large Scale Data Centers. Proceedings of the 8th ASME/AIAA Joint Thermophysics and Heat Transfer Conf., St. Louis, MO, June 2002.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Jerry Rolia
    • 1
  • Rich Friedrich
    • 1
  • Chandrakant Patel
    • 1
  1. 1.Hewlett Packard LabsPalo AltoUSA

Personalised recommendations