Journal of Grid Computing

, Volume 15, Issue 1, pp 127–137 | Cite as

An Evaluation of Information Consistency in Grid Information Systems

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Abstract

A Grid information system resolves queries that may need to consider all information sources (Grid services), which are widely distributed geographically, in order to enable efficient Grid functions that may utilise multiple cooperating services. Fundamentally this can be achieved by either moving the query to the data (query shipping) or moving the data to the query (data shipping). Existing Grid information system implementations have adopted one of the two approaches. This paper explores the two approaches in further detail by evaluating them to the best possible extent with respect to Grid information system benchmarking metrics. A Grid information system that follows the data shipping approach based on the replication of information that aims to improve the currency for highly-mutable information is presented. An implementation of this, based on an Enterprise Messaging System, is evaluated using the benchmarking method and the consequence of the results for the design of Grid information systems is discussed.

Keywords

Gird Information systems Query processing Service discovery 

References

  1. 1.
    Aiftimiei, C., Aimar, A., Ceccanti, A., Cecchi, M., Meglio, A.D., Estrella, F., Fuhrmam, P., Giorgio, E., Konya, B., Field, L., Nilsen, J.K., Riedel, M., White, J.: Towards next generations of software for distributed infrastructures: the european middleware initiative. In: Proceedings of the 8th International Conference on E-Science, pages 1–10, Chicago, IL, USA (2012)Google Scholar
  2. 2.
    Alonso, R., Barbara, D., Garcia-Molina, H.: Data caching issues in an information retrieval system. ACM Trans. Database Syst. 15(3), 359–384 (1990)CrossRefGoogle Scholar
  3. 3.
    Andreozzi, S., Burke, S., Field, L., Litmaath, M.: GLUE schema version 1.3Google Scholar
  4. 4.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern information retrieval. Addison Wesley, Harlow, England (1999)Google Scholar
  5. 5.
    Bird, I.: Computing for the large hadron collider. Annu. Rev. Nucl. Part. Sci. 61(1), 99–118 (2011)CrossRefGoogle Scholar
  6. 6.
    Bird, I., Jones, B., Kee, K.F.: The organization and management of grid infrastructures. Computer 42(1), 36–46 (2009)CrossRefGoogle Scholar
  7. 7.
    Casey, J., Cons, L., Lapka, W., Paladin, M., Skaburskas, K.: A messaging infrastructure for WLCG. J. Phys. Conf. Ser. 331(6), 062015 (2011)CrossRefGoogle Scholar
  8. 8.
    Cooke, A.W., Gray, A.J.G., Nutt, W., Magowan, J., Oevers, M., Taylor, P., Cordenonsi, R., Byrom, R., Cornwall, L., Djaoui, A., Field, L., Fisher, S.M., Hicks, S., Leake, J., Middleton, R., Wilson, A., Zhu, X., Podhorszki, N., Coghlan, B., Kenny, S., O’Callaghan, D., Ryan, J.: The Relational Grid Monitoring Architecture: Mediating Information about the Grid. J. Grid Comput. 2(4), 323–339 (2004)CrossRefMATHGoogle Scholar
  9. 9.
    David, M., Borges, G., Gomes, J., Pina, J., Plasencia, I.C., Castillo, E.F., Díaz, I., Fernandez, C., Freire, E., Simón, Ā., Koumantaros, K., Dreschner, M., Ferrari, T., Solagna, P.: Validation of Grid Middleware for the European Grid Infrastructure. J. Grid Comput. 12(3), 543–558 (2014)CrossRefGoogle Scholar
  10. 10.
    Ehm, F., Field, L., Schulz, M.W.: Scalability and performance analysis of the EGEE information system, vol. 119 (2008)Google Scholar
  11. 11.
    Ferrari, T., Gaido, L.: Resources and Services of the EGEE Production Infrastructure. J. Grid Comput. 9(2), 119–133 (2011)CrossRefGoogle Scholar
  12. 12.
    Field, L., Memon, S., Márton, I., Szigeti, G.: The EMI registry: Discovering services in a federated world. J. Grid Comput. 12(1), 29–40 (2014)CrossRefGoogle Scholar
  13. 13.
    Field, L., Sakellariou, R.: How dynamic is the grid? towards a quality metric for grid information systems. In: The proceedings of the 11th IEEE/ACM International Conference on Grid Computing, pages 113–120, Brussels, Belgium (2010)Google Scholar
  14. 14.
    Field, L., Sakellariou, R.: Benchmarking grid information systems. In: Proceedings of the 17th International Euro-Par Conference, volume 6852 of Lecture Notes in Computer Science, pages 479–490, Bordeaux, France (2011)Google Scholar
  15. 15.
    Fitzgerald, S., Foster, I., Kesselman, C., von Laszewski, G., Smith, W., Tuecke, S.: A directory service for configuring high-performance distributed computations. In: Proceedings of the Sixth IEEE International Symposium on High Performance Distributed Computing, pages 365–375, Portland, OR, USA (1997)Google Scholar
  16. 16.
    Kossmann, D.: The state of the art in distributed query processing. ACM Comput. Surv. 32(4), 422–469 (2000)CrossRefGoogle Scholar
  17. 17.
    Mastroianni, C., Talia, D., Verta, O.: Designing an information system for grids: Comparing hierarchical, decentralized p2p and super-peer models. Parallel Comput. 34(10), 593–611 (2008)CrossRefGoogle Scholar
  18. 18.
    Ordille, J.J., Miller, B.P.: Database challenges in global information systems. In: Proceedings of the ACM SIGMOD international conference on Management of data, pages 403–407, Washington, D.C., United States, p 1993 (1993)Google Scholar
  19. 19.
    Pordes, R., Petravick, D., Kramer, B., Olson, D., Livny, M., Roy, A., Avery, P., Blackburn, K., Wenaus, T., Wrthwein, F., Foster, I., Gardner, R., Wilde, M., Blatecky, A., McGee, J., Quick, R.: The open science grid. J. Phys. Conf. Ser., 78 (2007)Google Scholar
  20. 20.
    Rahman, R.M., Barker, K., Alhajj, R.: Replica Placement Strategies in Data Grid. J. Grid Comput. 6(1), 103–123 (2008)CrossRefMATHGoogle Scholar
  21. 21.
    Sakagami, H., Kamba, T., Sugiura, A., Koseki, Y.: Effective personalization of push-type systems - visualizing information freshness. Comp. Netw. ISDN Systems 30(1...7), 53–63 (1998). Proceedings of the Seventh International World Wide Web ConferenceCrossRefGoogle Scholar
  22. 22.
    Wolfson, O., Jajodia, S., Huang, Y.: An adaptive data replication algorithm. ACM Trans. Database Syst. 22(2), 255–314 (1997)CrossRefGoogle Scholar
  23. 23.
    Zanikolas, S., Sakellariou, R.: An importance-aware architecture for large-scale grid information services. Parallel Process. Letters 18(03), 347–370 (2008)MathSciNetCrossRefGoogle Scholar
  24. 24.
    Zhang, X., Freschl, J.L., Schopf, J.M.: A performance study of monitoring and information services for distributed systems. In: Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing, pages 270–281, Seattle, WA, USA (2003)Google Scholar
  25. 25.
    Zhang, X., Freschl, J., Schopf, J.M.: Scalability analysis of three monitoring and information systems: MDS2, r-GMA, and hawkeye. J. Parallel Distrib. Comput. 67(8), 883–902 (2007)CrossRefMATHGoogle Scholar
  26. 26.
    Zhang, X., Schopf, J.M.: Performance analysis of the globus toolkit monitoring and discovery service, MDS2. In: IEEE International Conference on Performance, Computing, and Communications, 2004, pages 843–849, Phoenix, AZ, USA (2004)Google Scholar

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© The Author(s) 2016

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.CERNGenevaSwitzerland
  2. 2.The University of ManchesterManchesterUK

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