Advertisement

Mathematical Service Discovery

  • Julian Padget
  • Omer Rana
Part of the IFIP The International Federation for Information Processing book series (IFIPAICT, volume 239)

Abstract

Matchmaking has been a subject of research for many years, but the increasing uptake of service-oriented computing, of which the Grid can be seen as a particular instance, has made effective and flexible matchmaking a necessity. Early approaches to matchmaking and current schemes in the Grid community, like ClassAds, take a syntactic point of view, essentially matching up literals or satisfying some simple constraints for the purpose of identifying computational resources. The increasing availability of web services shifts attention to the function of the service, but WSDL can only publish (limited) information about the signature of the operation which tells the client little about what the service actually does. The focus in the MONET (www.monet.nag.co.uk) and GENSS (genss.cs.bath.ac.uk) projects has been on describing the semantics of mathematical services and developing the means to search for suitable services given a problem description. In this paper we discuss (i) the schema extending WSDL that we call Mathematical Service Description Language (MSDL), (ii) a number of ontologies for describing various properties of mathematical services, (iii) an approach to describing pre-and post-conditions in OpenMath (www.openmath.org) and (iv) an extensible, generic match-making framework along with a suite of match plug-ins that are themselves web services.

Keywords

Service Discovery Software Agent Service Description Selection Policy Candidate Service 
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. 1.
    Stephen McGough Ali Anjomshoaa, Darren Pulsipher. Job Submission Description Language WG (JSDL-WG), 2003. Available from http://www.forge.gridforum.org/projects/jsdl-wg/.
  2. 2.
    Rebhi Baraka, Olga Caprotti, and Wolfgang Schreiner. A Web Registry for Publishing and Discovering Mathematical Services. In EEE, pages 190–193. IEEE Computer Society, 2005.Google Scholar
  3. 3.
    R.F. Boisvert, S.E. Howe, and D.K. Kahaner. GAMS: A Framework for the Management of Scientific Software. ACM Transactions on Mathematical Software, 11(4): 313–355, December 1985.Google Scholar
  4. 4.
    O. Bunin, Y. Guo, and J. Darlington. Design of problem-solving environment for contingent claim valuation. In Proceedings of EuroPar 2001, volume 2150 of LNCS. Springer Verlag, 2001.Google Scholar
  5. 5.
    Olga Caprotti, Michael Dewar, James Davenport, and Julian Padget. Mathematics on the (Semantic) Net. In Christoph Bussler, John Davies, Dieter Fensel, and Rudi Studer, editors, Proceedings of the European Symposium on the Semantic Web, volume 3053 of LNCS, pages 213–224. Springer Verlag, 2004. ISBN 3-540-21999-4.Google Scholar
  6. 6.
    John Darlington. Gridsam grid job submission and monitoring web service, http://www.omii.ac.uk/projects/, 2004. Last visited September 2006. See also http://www.lesc.ic.ac.uk/gridsam/
  7. 7.
    Tzvetan Drashansky, Elias N. Houstis, Naren Ramakrishnan, and John R. Rice. Networked agents for scientific computing. Communications of the ACM, 42(3): 48–54, 1999.CrossRefGoogle Scholar
  8. 8.
    S. Fleeter, E. Houstis, J. Rice, C. Zhou, and A. Catlin. A problem solving environment for simulating gas turbines. In Proceedings of 16th IMACS World Congress, pages 104–105, 2000.Google Scholar
  9. 9.
    G. Fox, D. Gannon, and M. Thomas. A summary of grid computing environments. Concurrency and Computation: Practice and Experience (Special Issue), 2003.Google Scholar
  10. 10.
    E. Gallopoulos, E. N. Houstis, and J. R. Rice. Computer as thinker/doer: Problem-solving environments for computational science. IEEE Computational Science and Engineering, 1(2), 1994.Google Scholar
  11. 11.
    M. Genesereth and R. Fikes. Knowledge Interchange Format, Version 3.0 Reference Manual. Technical report, Computer Science Department, Stanford University, 1992. Available from http://www.ksl.stanford.edu/knowledge-sharing/papers/ kif.ps.
  12. 12.
    Tom Goodale, Simone A. Ludwig, William Naylor, Julian Padget, and Omer F. Rana. Service-oriented matchmaking and brokerage. In Paul Watson, editor, Proceedings of UK e-Science All Hands conference. EPSRC, 2006.Google Scholar
  13. 13.
    D. Kuokka and L. Harada. Integrating information via matchmaking. Intelligent Information Systems 6(2-3), pp. 261–279, 1996.CrossRefGoogle Scholar
  14. 14.
    M. Li, O. F. Rana, D. W. Walker, M. Shields, and Y. Huang. Component-based Software Development, chapter Component-based Problem Solving Environments for Computational Science. World Scientific Publishing, 2003.Google Scholar
  15. 15.
    Phillip Lord, Pinar Alper, Chris Wroe, and Carole Goble. Feta: A light-weight architecture for user oriented semantic service discovery. In A. Gomez-Pérez and J.T Euzenat, editors, European Semantic Web Conference, pages 17–31. Springer-Verlag, 2005.Google Scholar
  16. 16.
    Simone Ludwig, Omer Rana, William Naylor, and Julian Padget. Matchmaking Framework for Mathematical Web Services. Journal of Grid Computing, 4(l): 33–48, March 2006. Available via http://www.dx.doi.org/10.1007/sl0723-005-9019-z. ISSN: 1570-7873 (Paper) 1572-9814 (Online).
  17. 17.
    W. Bohrer M. Nodine and A.H. Ngu. Semantic brokering over dynamic heterogenous data sources in InfoSleuth. In Proceedings of the 15th International Conference on Data Engineering, pp. 358–365, 1999.Google Scholar
  18. 18.
    William Naylor and Julian Padget. From untyped to polymorphically typed objects in mathematical web services. In William Farmer, editor, Proceedings of MKM2006. To appear in Springer LNCS, 2006.Google Scholar
  19. 19.
    Tom Oinn, Mark Greenwood, Matthew Addis, M. Nedim Alpdemir, Justin Ferris, Kevin Glover, Carole Goble, Antoon Goderis, Duncan Hull, Darren Marvin, Peter Li, Phillip Lord, Matthew R. Pocock, Martin Senger, Robert Stevens, Anil Wipat, and Chris Wroe. Taverna: lessons in creating a workflow environment for the life sciences: Research articles. Concurr. Comput.: Pract. Exper., 18(10): 1067–1100, 2006.CrossRefGoogle Scholar
  20. 20.
    Julian Padget. Knoogle matchmaking and brokerage framework, http://www.omii. ac.uk/projects/, 2006. Last visited September 2006.
  21. 21.
    D. Richardson. Some Unsolvable Problems Involving Elementary Functions of a Real Variable. Journal of Computational Logic, 33: 514–520, 1968.MATHGoogle Scholar
  22. 22.
    Daniel Richardson. The uniformity conjecture. In Jens Blanck, Vasco Brattka, and Peter Hertling, editors, CCA, volume 2064 of Lecture Notes in Computer Science, pages 253–272. Springer, 2000.Google Scholar
  23. 23.
    G. Salton. Automatic Text Processing. Addison-Wesley, 1989.Google Scholar
  24. 24.
    K. Sycara, S. Widoff, M. Klusch, and J. Lu. Larks: Dynamic matchmaking among heterogeneous software agents in cyberspace. Journal of Autonomous Agents and Multi Agent Systems, 5(2): 173–203, June 2002.Google Scholar
  25. 25.
    D. McKay, T. Finin, R. Fritzson and R. McEntire. KQML as an agent communication language. In Proceedings of 3rd International Conference on Information and Knowledge Management, pp. 456–463, 1994.Google Scholar
  26. 26.
    The OpenMath Society. The OpenMath Standard, June 2004. Available from http://www.openmath.org/standard/om2 0-20 04-0 6-30/omstd20.pdf.
  27. 27.
    D. Veit. Matchmaking in Electronic Markets, volume 2882 of LNCS. Springer, 2003. Hot Topics.Google Scholar
  28. 28.
    W3C. Web Services Description Language (WSDL) Version 1.2 W3C Working Draft. W3C, 2002-2003. Available from http://www.w3.org/TR/wsdll2.
  29. 29.
    Chris Wroe, Robert Stevens, Carole Goble, Angus Roberts, and Mark Greenwood. A suite of DAML+OIL Ontologies to Describe Bioinformatics Web Services and Data. The International Journal of Cooperative Information Systems, 12(2): 597–624, 2003.Google Scholar

Copyright information

© International Federation for Information Processing 2007

Authors and Affiliations

  • Julian Padget
    • 1
  • Omer Rana
    • 2
  1. 1.Department of Computer ScienceUniversity of BathBathUK
  2. 2.Department of Computer ScienceCardiff UniversityCardiffUK

Personalised recommendations