Skip to main content

A Distributed Service Oriented Framework for Metaheuristics Using a Public Standard

  • Chapter
Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)

Abstract

This work presents a Java-based environment that facilitates the development of distributed algorithms using the OSGi standard. OSGi is a plug-in oriented development platform that enables the installation, support and deployment of components that expose and use services dynamically. Using OSGi in a large research area, like the Heuristic Algorithms, facilitate the creation or modification of algorithms, operators or problems using its features: event administration, easy service implementation, transparent service distribution and lifecycle management. In this work, a framework based in OSGi is presented, and as an example two heuristics have been developed: a Tabu Search and a Distributed Genetic Algorithm.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alba, E., Almeida, F., Blesa, M., Cotta, C., Díaz, M., Dorta, I., Gabarró, J., León, C., Luque, G., Petit, J., Rodríguez, C., Rojas, A., Xhafa, F.: Efficient parallel LAN/WAN algorithms for optimization, the MALLBA project. Parallel Computing 32(5-6), 415–440 (2006)

    Article  Google Scholar 

  2. Alliance, O.: OSGi alliance (2004), http://www.osgi.org/

  3. Arenas, M., Collet, P., Eiben, A., Jelasity, M., Merelo, J.J., Paechter, B., Preuß, M., Schoenauer, M.: A framework for distributed evolutionary algorithms. In: Guervós, J.J.M., Adamidis, P.A., Beyer, H.-G., Fernández-Villacañas, J.-L., Schwefel, H.-P. (eds.) PPSN 2002. LNCS, vol. 2439, pp. 665–675. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  4. BranchAndCutorg. Vehicle routing data sets (2003), http://branchandcut.org/VRP/data/

  5. Buyya, R.: High Performance Cluster Computing: Architectures and Systems. Prentice-Hall, Englewood Cliffs (1999)

    Google Scholar 

  6. Cahon, S., Melab, N., Talbi, E.: ParadisEO: A framework for the reusable design of parallel and distributed metaheuristics. Journal of Heuristics 10(3), 357–380 (2004)

    Article  Google Scholar 

  7. Escoffier, C., Donsez, D., Hall, R.S.: Developing an OSGi-like Service Platform for .NET. In: 3rd IEEE Consumer Communications and Networking Conference, vol. 1-3, pp. 213–217 (2006)

    Google Scholar 

  8. Esparcia-Alcázar, A.I., Cardós, M., Merelo, J.J., Martínez-García, A., García-Sánchez, P., Alfaro-Cid, E., Sharman, K.: EVITA: An integral evolutionary methodology for the inventory and transportation problem. Studies in Computational Intelligence 161, 151–172 (2009)

    Article  Google Scholar 

  9. Foster, I.: The Grid: A new infrastructure for 21st Century Science. Phisics Today 55, 42–47 (2002)

    Article  Google Scholar 

  10. Gaspero, L., Schaerf, A.: Easylocal++: an object-oriented framework for the flexible desgin of local search algorithms and metaheuristics. In: Proceedings of 4th Metaheuristics International Conference (MIC 2001), pp. 287–292 (2001)

    Google Scholar 

  11. González, J.R., Pelta, D.A., Masegosa, A.D.: A framework for developing optimization-based decision support systems. Expert Systems with Applications 36(3, Part 1), 4581–4588 (2009)

    Article  Google Scholar 

  12. Kriens, P.: Research challenges for OSGi (2008), http://www.osgi.org/blog/2008/02/research-challenges-for-osgi.html

  13. León, C., Miranda, G., Segura, C.: Metco: A parallel plugin-based framework for multi-objective optimization. International Journal on Artificial Intelligence Tools 18(4), 569–588 (2009)

    Article  Google Scholar 

  14. Luke, S., et al.: ECJ: A Java-based Evolutionary Computation and Genetic Programming Research System (2009), http://www.cs.umd.edu/projects/plus/ec/ecj

  15. Marples, D., Kriens, P.: The Open Services Gateway Initiative: An introductory overview. IEEE Communications Magazine 39(12), 110–114 (2001)

    Article  Google Scholar 

  16. Miller, B.A., Nixon, T., Tai, C., Wood, M.D.: Home networking with universal plug and play. IEEE Communications Magazine 39(12), 104–109 (2001)

    Article  Google Scholar 

  17. OSGi Alliance. Declarative services specification, pp. 281–314 (2007), http://www.osgi.org/download/r4-v4.2-cmpn-draft-20090310.pdf

  18. Papazoglou, M.P., Van Den Heuvel, W.: Service oriented architectures: Approaches, technologies and research issues. VLDB Journal 16(3), 389–415 (2007)

    Article  Google Scholar 

  19. Rellermeyer, J.S., Alonso, G., Roscoe, T.: R-osgi: Distributed applications through software modularization. In: Cerqueira, R., Campbell, R.H. (eds.) Middleware 2007. LNCS, vol. 4834, pp. 1–20. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  20. Wagner, S., Affenzeller, M.: Heuristiclab grid - a flexible and extensible environment for parallel heuristic optimization. In: Proceedings of the International Conference on Systems Science, vol. 1, pp. 289–296 (2004)

    Google Scholar 

  21. Wagner, S., Winkler, S., Pitzer, E., Kronberger, G., Beham, A., Braune, R., Affenzeller, M.: Benefits of plugin-based heuristic optimization software systems. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds.) EUROCAST 2007. LNCS, vol. 4739, pp. 747–754. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  22. Waldo, J.: The Jini architecture for network-centric computing. Communications of the ACM 42(7), 76–82 (1999)

    Article  Google Scholar 

  23. Wall, B.: A genetic algorithm for resource-constrained scheduling, Ph.D. thesis. MIT, Cambridge (1996), http://lancet.mit.edu/ga

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

García-Sánchez, P. et al. (2010). A Distributed Service Oriented Framework for Metaheuristics Using a Public Standard. In: González, J.R., Pelta, D.A., Cruz, C., Terrazas, G., Krasnogor, N. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2010). Studies in Computational Intelligence, vol 284. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12538-6_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-12538-6_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12537-9

  • Online ISBN: 978-3-642-12538-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics