The Journal of Supercomputing

, Volume 38, Issue 3, pp 279–305 | Cite as

Flexible Grid service management through resource partitioning

  • Bruno Volckaert
  • Pieter Thysebaert
  • Marc De Leenheer
  • Filip De Turck
  • Bart Dhoedt
  • Piet Demeester
Article

Abstract

In this paper, a distributed and scalable Grid service management architecture is presented. The proposed architecture is capable of monitoring task submission behaviour and deriving Grid service class characteristics, for use in performing automated computational, storage and network resource-to-service partitioning. This partitioning of Grid resources amongst service classes (each service class is assigned exclusive usage of a distinct subset of the available Grid resources), along with the dynamic deployment of Grid management components dedicated and tuned to the requirements of a particular service class introduces the concept of Virtual Private Grids. We present two distinct algorithmic approaches for the resource partitioning problem, the first based on Divisible Load Theory (DLT) and the second built on Genetic Algorithms (GA). The advantages and drawbacks of each approach are discussed and their performance is evaluated on a sample Grid topology using NSGrid, an ns-2 based Grid simulator. Results show that the use of this Service Management Architecture in combination with the proposed algorithms improves computational and network resource efficiency, simplifies schedule making decisions, reduces the overall complexity of managing the Grid system, and at the same time improves Grid QoS support (with regard to job response times) by automatically assigning Grid resources to the different service classes prior to scheduling.

Keywords

Grid service management Virtual private Grid Service Grids 

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References

  1. 1.
    Foster I, Kesselman C, Nick JM, Tuecke S (2002) Grid services for distributed system integration. IEEE Computer 35(6):37–46Google Scholar
  2. 2.
    Enabling Grids for E-Science in Europe. website, http://egee-intranet.web.cern.ch
  3. 3.
    Foster I et al (2005) The open Grid services architecture, version 1.0. draft-ggf-OGSA-spec-019, http://forge.gridforum.org/projects/ogsa-wg
  4. 4.
    Czajkowski K et al., The WS-Resource framework version 1.0. draft, http://www.globus.org/wsrf/specs/ws-wsrf.pdf
  5. 5.
    Kephart JO, Chess DM (2003) The vision of autonomic computing. IEEE Computer 36(1):41–50Google Scholar
  6. 6.
    Ganek AG, Corbi TA (2003) The dawning of the autonomic computing era. IBM Systems Journal 42(1):5–18CrossRefGoogle Scholar
  7. 7.
    Volckaert B, Thysebaert P, De Turck F, Demeester P, Dhoedt B (2003) Evaluation of Grid scheduling strategies through a network-aware grid simulator. In: Proc. of PDPTA 2003 Vol. 1, pp. 31–35Google Scholar
  8. 8.
    Ranganathan K, Foster I (2003) Simulation studies of computation and data scheduling algorithms for data grids. Journal of Grid Computing 1(1):53–62CrossRefGoogle Scholar
  9. 9.
    Berman F et al. (2003) Adaptive computing on the Grid using apples. IEEE Transactions on Parallel and Distributed Systems 14(4):69–382CrossRefGoogle Scholar
  10. 10.
    Dail H, Berman F, Casanova H (2003) A decoupled scheduling aproach for grid application development environments. Journal of Parallel and Distributed Computing 63(5):505–524MATHCrossRefGoogle Scholar
  11. 11.
    Wolski R, Spring N, Hayes J (1999) The network weather service: A distributed resource performance forecasting service for metacomputing. Journal of Future Generation Computing Systems 15(5–6)Google Scholar
  12. 12.
    Czajkowski K, Fitzgerald S, Foster I, Kesselman C (2001) Grid information services for distributed resource sharing. In: Proc. of the 10th IEEE International Symposium on High-Performance Distributed ComputingGoogle Scholar
  13. 13.
    Foster I, Roy A, Sander V (2000) A quality of service architecture that combines resource reservation and application adaptation. In: Proc. of the eighth international workshop on quality of service (IWQoS 2000)Google Scholar
  14. 14.
    Rodger A (2004) Analyst report: Butler group subscription services: Technology infrastructure—IBM Tivoli intelligent orchestrator and IBM tivoli provisioning manager. ftp://ftp.software.ibm.com/software/tivoli/analystreports/ar-orch-prov-butler.pdfGoogle Scholar
  15. 15.
    Lee HL, et al (2004) A resource manager for optimal resource selection and fault tolerance service in Grids. CCGrid 2004, pp 572–579Google Scholar
  16. 16.
    Thysebaert P, Volckaert B, De Turck F, Dhoedt B, Demeester P (2004) Network aspects of Grid scheduling algorithms. In: Proc. of PDCS 11Google Scholar
  17. 17.
    Hovestadt M, Kao O, Keller A, Streit A (2003) Scheduling in HPC resource management systems: Queueing vs. planning. In: Proc. of the 9th Workshop on Job Scheduling Strategies for Parallel Processing, Feitelson DG, and Rudolph L (eds), Springer LNCS 2862Google Scholar
  18. 18.
    Yu D, Robertazzi TG (2003) Divisible load scheduling for Grid computing. In: Proc. of the IASTED 2003 International Conference on Parallel and Distributed Computing and Systems (PDCS)Google Scholar
  19. 19.
    Thysebaert P, De Turck F, Dhoedt B, Demeester P (2005) Using divisible load theory to dimension optical transport networks for computational grids. In: Proc. of OFC/NFOECGoogle Scholar
  20. 20.
    Kitatsuji Y, Kobayashi K, Kitamura Y et al (2002) Deployment of APAN Tokyo XP and evaluation of source based routing. Transactions of the Institute of Electronics, Information and Communication Engineers B J85-B(8):1164–1171Google Scholar
  21. 21.
    LHC Computing Grid project, website, http://lcg.web.cern.ch/LCG
  22. 22.
    The Network Simulator-NS2, website, http://www.isi.edu/nsnam/ns
  23. 23.
    Lu D, Dinda P (2003) GridG: Generating realistic computational Grids. Performance Evaluation Review 30(4)Google Scholar
  24. 24.
    Grefenstette JJ (1986) Optimization of control parameters for genetic algorithms. IEEE Trans. Systems, Man, and Cybernetics 16(1):122–128Google Scholar

Copyright information

© Springer Science + Business Media, LLC 2006

Authors and Affiliations

  • Bruno Volckaert
    • 1
  • Pieter Thysebaert
    • 1
  • Marc De Leenheer
    • 1
  • Filip De Turck
    • 1
  • Bart Dhoedt
    • 1
  • Piet Demeester
    • 1
  1. 1.Department of Information TechnologyGhent UniversityGentBelgium

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