Skip to main content
SpringerLink
Log in

Midland: a service-oriented cluster computing infrastructure

  • Original Research Paper
  • Published:
Service Oriented Computing and Applications Aims and scope Submit manuscript

Abstract

Midland is a service-oriented software infrastructure that enables the clustering of arbitrarily large collections of computing resources. The resulting clusters may be integrated to form an open, dynamically configurable computational grid system where each cluster defines a self-reliant and independent management domain. Web Services make up the primary integration mechanism both at the cluster and grid levels, respectively. This is complemented by a light XML based messaging protocol exclusively used for cluster bound interactions. The paper describes Midland’s architecture, and the service-oriented approach taken to develop the associated resource management mechanisms. It also includes an exposition of the model of service capacity which is one of the enablers of the service-centric strategy underlying the cluster management mechanisms. The operational performance of Midland is illustrated experimentally in the context of a Grid test-bed comprising three clusters. The experimental results highlight the performance of the model of service capacity as well as some aspects of Midland operational performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Thain D, Tannenbaum T, Livny M (2005) Distributed computing in practice: the Condor experience. Concurrency Comput Pract Exper 17: 323–356. doi:10.1002/cpe.938

    Article  Google Scholar 

  2. Zhou S, Zheng X, Wang J, Delisle P (1993) Utopia: a load sharing facility for large, heterogeneous distributed computer systems. Softw Pract Exper 23: 224–234

    Article  Google Scholar 

  3. Holt G (2005) Time-critical scheduling on a well utilised HPC system at ECMWF using loadleveler with resource reservation. In: Lecture Notes in Computer Science, pp 102–124

  4. Grimshaw AS, Natrajan A (2005) Legion: lessons learned building a grid operating system. Proc IEEE 93: 589–603. doi:10.1109/JPROC.2004.842764

    Article  Google Scholar 

  5. Romberg M (2002) The UNICORE grid infrastructure. Sci Prog 10: 149–157

    Google Scholar 

  6. Chen D, Demichev A, Foster D, Kalyaev V, Kryukov A, Lamanna M, Pose V, Rocha R, Wang C (2004) OGSA Globus Toolkits evaluation activity at CERN. In: Nuclear instruments and methods in physics research, Section A: accelerators, spectrometers, detectors and associated equipment, pp 80–84

  7. Henderson RL (1995) Job scheduling under the Portable Batch System. In: Lecture Notes in Computer Science. Springer Verlag, Heidelberg, pp 279–294

  8. Foster I (2006) Globus Toolkit Version 4: Software for Service-Oriented Systems. J Comput Sci Technol 21: 513–520. doi:10.1007/s11390-006-0513-y

    Article  Google Scholar 

  9. Farantos SC, Stamatiadis S, Nellari N, Maric D (2002) Grid enabling technology. ENACTS

  10. Miura K (2004) Overview of Japanese National Research Grid Initiative (NAREGI) project. Fujitsu Sci Tech J 40: 196–204

    Google Scholar 

  11. Bernholdt D et al (2005) The earth system grid: supporting the next generation of climate modeling research. Proc IEEE 93: 485–495. doi:10.1109/JPROC.2004.842745

    Article  Google Scholar 

  12. Avery P, Foster I (2001) The GriPhyN Project: toward petascale virtual data grids

  13. Boden T (2004) The grid enterprise-Structuring the agile business of the future. BT Technol J 22: 107–117. doi:10.1023/B:BTTJ.0000015501.06794.97

    Article  Google Scholar 

  14. Crawford CH, Bate GP, Cherbakov L, Holley KL, Tsocanos C (2005) Toward an on demand service-oriented architecture. IBM Syst J 44: 81–107

    Article  Google Scholar 

  15. Joseph J, Ernest M, Fellenstein C (2004) Evolution of grid computing architecture and grid adoption models. IBM Syst J 43: 624–645

    Google Scholar 

  16. Leff A, Rayfield JT, Dias DM (2003) Service-level agreements and commercial grids. IEEE Internet Comput 7: 44–50. doi:10.1109/MIC.2003.1215659

    Article  Google Scholar 

  17. GGF Open Grid Services Architecture (OGSA) (2004) Global Grid Forum

  18. Czajkowski K, Foster I, Kesselman C (2005) Agreement-based resource management. Proc IEEE 93: 631–643. doi:10.1109/JPROC.2004.842773

    Article  Google Scholar 

  19. Burchard L-O, Hovestadt M, Kao O, Keller A, Linnert B (2004) The virtual resource manager: an architecture for SLA-aware resource management. In: 2004 IEEE International Symposium on Cluster Computing and the Grid. CCGrid, pp 126–133

  20. Fox G (2003) Integrating computing and information on grids. Comput Sci Eng 5: 94–96. doi:10.1109/MCISE.2003.1208650

    Article  Google Scholar 

  21. OASIS Web Services Resource Framework (WSRF) (2005) http://docs.oasis-open.org/wsrf/wsrf-primer-1.2-primer-cd-01.pdf

  22. Zhang X, Schopf JM (2004) Performance analysis of the Globus toolkit monitoring and discovery service, MDS2. In: IEEE international performance. Computing and communications conference, Chicago, pp 843–849

  23. Graupner S, Kotov V, Andrzejak A, Trinks H (2002) Control Architecture for Service Grids in a Federation of Utility Data Centers. HP Labs

  24. Faloutsos M, Faloutsos P, Faloutsos C (1999) On power-law relationships of the Internet topology. Comput Commun Rev 29: 251–262. doi:10.1145/316194.316229

    Article  Google Scholar 

  25. Barabási A, Albert R (1999) Emergence of Scaling in Random Networks. Science 286: 509–512. doi:10.1126/science.286.5439.509

    Article  MathSciNet  Google Scholar 

  26. Ripeanu M, Iamnitchi A, Foster I (2002) Mapping the Gnutella network. IEEE Internet Comput 6: 50–57

    Google Scholar 

  27. Derbal Y (2006) A new fault-tolerance framework for grid computing. Multiagent Grid Syst 2: 115–133

    MATH  Google Scholar 

  28. Desktop Management Task Force Common Information Model (CIM) (1999) http://www.dmtf.org/spec/cims.html

  29. Derbal Y (2008) Confidence-based grid service discovery. Int J Web Grid Serv 4: 189–210. doi:10.1504/IJWGS.2008.018887

    Article  Google Scholar 

  30. Derbal Y (2006) Entropic grid scheduling. J Grid Comput 4: 373–394. doi:10.1007/s10723-006-9034-8

    Article  MATH  Google Scholar 

  31. Derbal Y (2006) A probabilistic scheduling heuristic for computational grids. Multiagent Grid Syst 2: 45–59

    MATH  Google Scholar 

  32. Derbal Y (2005) Probabilistic resource state estimation in networked environments: the case of computational grids. In: Proceedings of the third annual conference on communication networks and services research (CNSR 2005). Halifax, Nova Scotia, pp 189–194

  33. Windows Management Instrumentation (WMI). http://www.microsoft.com/whdc/system/pnppwr/wmi/default.mspx

  34. Wolski R, Spring NT, Hayes J (1999) The Network Weather Service: a distributed resource performance forecasting service for metacomputing. J Future Gener Comput Syst 15: 757–768. doi:10.1016/S0167-739X(99)00025-4

    Article  Google Scholar 

  35. El-Ghazawi T, Gaj K, Alexandridis N, Vroman F, Nguyen N, Radzikowski JR, Samipagdi P, Suboh SA (2004) A performance study of job management systems. Concurrency Comput Pract Exper 16: 1229–1246. doi:10.1002/cpe.753

    Article  Google Scholar 

  36. Berman F, Wolski R, Casanova H, Cirne W, Dail H, Faerman M, Figueira S, Hayes J, Obertelli G, Schopf J, Shao G, Smallen S, Spring N, Su A, Zagorodnov D (2003) Adaptive computing on the grid using AppLeS. IEEE Trans Parallel Distrib Syst 14: 369–382. doi:10.1109/TPDS.2003.1195409

    Article  Google Scholar 

  37. W3C, SOAP Version 1.2 Part 0: Primer (2002) http://www.w3.org/TR/soap12-part0/

  38. Czajkowski K, Foster I, Karonis N, Kesselman C, Martin S, Smith W, Tuecke S (1998) A resource management architecture for metacomputing systems. In: Lecture Notes in Comuter Science, vol 1459, pp 62–82

  39. Zhou S (1992) LSF: load sharing in large-scale heterogeneous distributed systems. In: Proceedings of the 1992 workshop on cluster computing. Tallahassee, Florida

  40. Litzkow MJ, Livny M, Mutka MW (1988) Condor-a hunter of idle workstations. In: Proceedings of the international conference on distributed computing systems, San Jose, pp 104–111

  41. Graupner S, Kotov V, Andrzejak A, Trinks H (2003) Service-centric globally distributed computing. IEEE Internet Comput 7: 36–43. doi:10.1109/MIC.2003.1215658

    Article  Google Scholar 

  42. Beverly Yang B, Garcia-Molina H (2003) Designing a super-peer network. In: 19th International conference on data engineering Bangalore, pp 49–60

  43. Fox G, Pallickara S, Rao X (2005) Towards enabling peer-to-peer Grids. Concurrency Comput Pract Exper 17: 1109–1131. doi:10.1002/cpe.863

    Article  Google Scholar 

  44. Mastroianni C, Talia D, Verta O (2005) A super-peer model for resource discovery services in large-scale Grids. Future Gener Comput Syst 21: 1235–1248. doi:10.1016/j.future.2005.06.001

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Ted Rogers School of Information Technology Management, Ryerson University, Toronto, Canada

    Youcef Derbal

Authors
  1. Youcef Derbal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Youcef Derbal.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Derbal, Y. Midland: a service-oriented cluster computing infrastructure. SOCA 3, 109–125 (2009). https://doi.org/10.1007/s11761-009-0042-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11761-009-0042-y

Keywords

Search

Navigation