[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Springer Nature Link
Log in

Preference–Based Matchmaking of Grid Resources with CP–Nets

  • Published:
Journal of Grid Computing Aims and scope Submit manuscript

Abstract

We deal with the problem of preference-based matchmaking of computational resources belonging to a Grid. We introduce CP–Nets, a recent development in the field of Artificial Intelligence, as a means to deal with user’s preferences in the context of Grid scheduling. We discuss CP–Nets from a theoretical perspective and then analyze, qualitatively and quantitatively, their impact on the matchmaking process, with the help of a Grid simulator we developed for this purpose. Many different experiments have been setup and carried out, and we report here our main findings and the lessons learnt.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Anjomshoaa, A., Brisard, F., Drescher, M., Fellows, D., Ly, A., McGough, S., Pulsipher, D., Savva, A.: Job submission description language (jsdl), specification, version 1.0. Global Grid Forum Working Draft (2005)

  2. Azzedin, F., Maheswaran, M., Mitra, A.: Trust brokering and its use for resource matchmaking in public-resource Grids. J. Grid Computing 4, 247–263 (2006)

    Article  MATH  Google Scholar 

  3. Bai, X., Yu, H., Ji, Y., Marinescu, D.C.: Resource matching and a matchmaking service for an intelligent Grid. In: International Conference on Computational Intelligence, pp. 262–265 (2004)

  4. Bai, X., Yu, H., Wang, G., Ji, Y., Marinescu, D., Bölöni, L.: Intelligent Grids. In: Grid Computing: Software Environments and Tools, pp. 45–74. Springer (2005)

  5. Bayardo, R.J. Jr., Bohrer, W., Brice, R., Cichocki, A., Fowler, J., Helal, A., Kashyap, V., Ksiezyk, T., Martin, G., Nodine, M., Rashid, M., Rusinkiewicz, M., Shea, R., Unnikrishnan, C., Unruh, A., Woelk, D.: Infosleuth: agent-based semantic integration of information in open and dynamic environments. SIGMOD Rec. 26(2), 195–206 (1997)

    Article  Google Scholar 

  6. Boutilier, C., Brafman, R.I., Domshlak, C., Hoos, H.H., Poole, D.: Cp-nets: a tool for representing and reasoning with conditional ceteris paribus preference statements. J. Artif. Intell. Res. 21, 135–191 (2004)

    MathSciNet  MATH  Google Scholar 

  7. Boutilier, C., Brafman, R.I., Hoos, H.H., Poole, D.: Reasoning with conditional ceteris paribus preference statements. In: Laskey, K.B., Prade, H. (eds.) UAI, pp. 71–80. Morgan Kaufmann (1999)

  8. Buyya, R., Murshed, M.: Gridsim: a toolkit for the modeling and simulation of distributed resource management and scheduling for Grid computing. Concurr. Comput.: Pract. Exper. 14(13–15), 1175–1220 (2002)

    Article  MATH  Google Scholar 

  9. Cameron, D.G., Millar, A.P., Nicholson, C., Carvajal-Schiaffino, R., Stockinger, K., Zini, F.: Analysis of scheduling and replica optimisation strategies for data Grids using optorsim. J. Grid Computing 2(1), 57–69 (2004)

    Article  Google Scholar 

  10. Casanova, H., Legrand, A., Quinson, M.: Simgrid: a generic framework for large-scale distributed experiments. In: Proceedings of the 10th International Conference on Computer Modeling and Simulation, UKSIM ’08, pp. 126–131. IEEE Computer Society (2008)

  11. Clematis, A., Corana, A., D’Agostino, D., Galizia, A., Quarati, A.: Job-resource matchmaking on Grid through two-level benchmarking. Future Gener. Comput. Syst. 26(8), 1165–1179 (2010)

    Article  Google Scholar 

  12. Czajkowski, K., Fitzgerald, S., Foster, I., Kesselman, C.: Grid information services for distributed resource sharing. In: Proceedings of 10th IEEE International Symposium on High Performance Distributed Computing, 2001, pp. 181–194 (2001)

  13. Dail, H., Sievert, O., Berman, F., Casanova, H., YarKhan, A., Vadhiyar, S., Dongarra, J., Liu, C., Yang, L., Angulo, D., Foster, I.: Scheduling in the Grid application development software project. In: Nabrzyski, J., Schopf, J.M., Weglarz, J. (eds.) Grid Resource Management, pp. 73–98. Kluwer Academic Publishers, Norwell, MA, USA (2004)

    Chapter  Google Scholar 

  14. Dumitrescu, C., Foster, I.: Usage policy-based cpu sharing in virtual organizations. In: Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing, GRID ’04, pp. 53–60. IEEE Computer Society, Washington, DC, USA (2004)

    Chapter  Google Scholar 

  15. Elmroth, E., Tordsson, J.: Grid resource brokering algorithms enabling advance reservations and resource selection based on performance predictions. Future Gener. Comput. Syst. 24, 585–593 (2008)

    Article  Google Scholar 

  16. Foster, I., Kesselman, C.: The Grid. Blueprint for a New Computing Infrastructure (Elsevier Series in Grid Computing), 2nd edn., Morgan-Kaufmann (2003)

  17. Foster, I., Kesselman, C., Tuecke, S.: The anatomy of the Grid: enabling scalable virtual organizations. Int. J. High Perform. Comput. Appl. 15(3), 200–222 (2001)

    Article  Google Scholar 

  18. Harth, A., Decker, S., He, Y., Tangmunarunkit, H., Kesselman, C.: A semantic matchmaker service on the Grid. In: Proceedings of the 13th international World Wide Web Conference on Alternate Track Papers & Posters, WWW Alt. ’04, pp. 326–327. ACM (2004)

  19. Iosup, A., Epema, D.: Grenchmark: a framework for analyzing, testing, and comparing Grids. In: IEEE International Symposium on Cluster Computing and the Grid, pp. 313–320. IEEE Computer Society (2006)

  20. Klusáček, D., Rudová, H.: Alea 2: job scheduling simulator. In: Proceedings of the 3rd International ICST Conference on Simulation Tools and Techniques, SIMUTools ’10, vol. 61, pp. 1–61:10, ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering). Brussels, Belgium, Belgium (2010)

  21. Kotani, Y., Ino, F., Hagihara, K.: A resource selection system for cycle stealing in gpu Grids. J. Grid Computing 6, 399–416 (2008)

    Article  Google Scholar 

  22. Kuokka, D., Harada, L.: Matchmaking for information agents. In: Proceedings of the 14th International Joint Conference on Artificial Intelligence-IJCAI’95, vol. 1, pp. 672–678. Morgan Kaufmann Publishers Inc. (1995)

  23. Kurowski, K., Nabrzyski, J., Oleksiak, A., Weglarz, J.: Grid scheduling simulations with gssim. In: Proceedings of the 13th International Conference on Parallel and Distributed Systems-ICPADS ’07, vol. 02, pp. 1–8. IEEE Computer Society (2007)

  24. Lamehamedi, H., Shentu, Z., Szymanski, B., Deelman, E.: Simulation of dynamic data replication strategies in data Grids. In: Proceedings of International Parallel and Distributed Processing Symposium, 2003, pp. 10 (2003)

  25. Li, H., Buyya, R.: Model-driven simulation of Grid scheduling strategies. In: Proceedings of the 3rd IEEE International Conference on e-Science and Grid Computing, pp. 287–294. IEEE Computer Society. Washington, DC, USA (2007)

    Google Scholar 

  26. Li, H., Buyya, R.: Model-based simulation and performance evaluation of Grid scheduling strategies. Future Gener. Comput. Syst. 25, 460–465 (2009)

    Article  Google Scholar 

  27. Liu, C., Foster, I.: A constraint language approach to matchmaking. In: Proceedings of the 14th International Workshop on Research Issues on Data Engineering: Web Services for E-Commerce and E-Government Applications (RIDE’04), RIDE ’04, pp. 7–14. IEEE Computer Society (2004)

  28. Liu, C., Yang, L., Foster, I., Angulo, D.: Design and evaluation of a resource selection framework for Grid applications. In: Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing, HPDC ’02, pp. 63. IEEE Computer Society (2002)

  29. Lublin, U., Feitelson, D.G.: The workload on parallel supercomputers: modeling the characteristics of rigid jobs. J. Parallel Distrib. Comput. 63, 1105–1122 (2003)

    Article  MATH  Google Scholar 

  30. Ludwig, S., Rana, O., Padget, J., Naylor, W.: Matchmaking framework for mathematical web services. J. Grid Computing 4, 33–48 (2006)

    Article  Google Scholar 

  31. Medernach, E.: Workload analysis of a cluster in a Grid environment. In: Feitelson, D., Frachtenberg, E., Rudolph, L., Schwiegelshohn, U. (eds.) Job Scheduling Strategies for Parallel Processing of Lecture Notes in Computer Science, vol. 3834, pp. 36–61. Springer Berlin/Heidelberg (2005)

    Chapter  Google Scholar 

  32. Naqvi, S., Riguidel, M.: Grid security services simulator (g3s) — a simulation tool for the design and analysis of Grid security solutions. In: Proceedings of the 1st International Conference on e-Science and Grid Computing, E-SCIENCE ’05, pp. 421–428. IEEE Computer Society (2005)

  33. Nassif, L.N., Nogueira, J.M., de Andrade, F.V.V.: Resource selection in Grid: a taxonomy and a new system based on decision theory, case-based reasoning, and fine-grain policies. Concurr. Comput.: Pract. Exper. 21, 337–355 (2009)

    Article  Google Scholar 

  34. Pacini, F.: Job submission description language attributes, glite specification (submission through wmproxy service). egee-jra1-tec-590869-jdlattributes-v0-8. EGEE (2006)

  35. Paolucci, M., Srinivasan, N., Sycara, K.P., Nishimura, T.: Towards a semantic choreography of web services: from wsdl to daml-s. In: Proceedings of the International Conference on Web Services, ICWS ’03, pp. 22–26. Las Vegas, Nevada, USA. CSREA Press, 23–26 June 2003

  36. Ranganathan, K., Foster, I.: Computation scheduling and data replication algorithms for data Grids. In: Nabrzyski, J., Schopf, J.M., Weglarz, J. (eds.) Grid Resource Management, pp. 359–373. Kluwer Academic Publishers (2004)

  37. Sfiligoi, I., Bradley, D.C., Holzman, B., Mhashilkar, P., Padhi, S., Wurthwein, F.: The pilot way to Grid resources using glideinwms. In: Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering-CSIE ’09, vol. 02, pp. 428–432. IEEE Computer Society (2009)

  38. Singh, N.: A common lisp api and facilitator for absi: version 2.0.3. Technical Report Logic-93-4, Logic Group, Computer Science Department. Stanford University (1993)

  39. Solomon, M.: The Classad Language Reference Manual v2.1. Computer Sciences Department. University of Wisconsin, Madison, USA (2003)

    Google Scholar 

  40. Song, H.J., Liu, X., Jakobsen, D., Bhagwan, R., Zhang, X., Taura, K., Chien, A.: The microgrid: a scientific tool for modeling computational Grids. Sci. Program. 8(3), 127–141 (2000)

    Google Scholar 

  41. Subrahmanian, V.S., Bonatti, P., Dix, U.J., Eiter, T., Kraus, S., Ross, R.: Heterogeneous Agent Systems. MIT Press (2000)

  42. Sycara, K., Lu, J., Klusch, M.: Interoperability among heterogeneous software agents on the internet. Technical Report CMU-RI-TR-98-22, Robotics Institute. Pittsburgh, PA (1998)

  43. Sycara, K., Widoff, S., Klusch, M., Lu, J.: Larks: Dynamic matchmaking among heterogeneous software agents in cyberspace. Auton. Agent Multi-Agent Syst. 5(2), 173–203 (2002)

    Article  Google Scholar 

  44. Takefusa, A., Matsuoka, S., Nakada, H., Aida, K., Nagashima, U.: Overview of a performance evaluation system for global computing scheduling algorithms. In: Proceedings of the 8th International Symposium on High Performance Distributed Computing, pp. 97–104 (1999)

  45. Thain, D., Tannenbaum, T., Livny, M.: Condor and the Grid. In: Berman, F., Fox, G., Hey, T. (eds.) Grid Computing: Making the Global Infrastructure a Reality. Wiley (2002)

  46. Thysebaert, P., Volckaert, B., de Turck, F., Dhoedt, B., Demeester, P.: Evaluation of Grid scheduling strategies through nsgrid: a network-aware Grid simulator. Neural Parallel Sci. Comput. 12(3), 353–378 (2004)

    Google Scholar 

  47. Wang, C.-M., Chen, H.-M., Hsu, C.-C., Lee, J.: Dynamic resource selection heuristics for a non-reserved bidding-based Grid environment. Future Gener. Comput. Syst. 26, 183–197 (2010)

    Article  Google Scholar 

  48. Wickler, G.J.: Using expressive and flexible action representations to reason about capabilities for intelligent agent cooperation. PhD thesis, University of Edinburgh (1999)

Download references

Author information

Authors and Affiliations

  1. University of Salento, Lecce, Italy

    Massimo Cafaro & Giovanni Aloisio

  2. CMCC—Euro-Mediterranean Centre on Climate Change, Lecce, Italy

    Massimo Cafaro, Maria Mirto & Giovanni Aloisio

Authors
  1. Massimo Cafaro
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maria Mirto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Giovanni Aloisio
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Massimo Cafaro.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cafaro, M., Mirto, M. & Aloisio, G. Preference–Based Matchmaking of Grid Resources with CP–Nets. J Grid Computing 11, 211–237 (2013). https://doi.org/10.1007/s10723-012-9235-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10723-012-9235-2

Keywords

Search

Navigation