CFP last date
22 April 2024
Reseach Article

Building a Truly Distributed Constraint Solver with JADE

by Ibrahim Adeyanju
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 46 - Number 8
Year of Publication: 2012
Authors: Ibrahim Adeyanju
10.5120/6925-9319

Ibrahim Adeyanju . Building a Truly Distributed Constraint Solver with JADE. International Journal of Computer Applications. 46, 8 ( May 2012), 1-7. DOI=10.5120/6925-9319

@article{ 10.5120/6925-9319,
author = { Ibrahim Adeyanju },
title = { Building a Truly Distributed Constraint Solver with JADE },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 46 },
number = { 8 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume46/number8/6925-9319/ },
doi = { 10.5120/6925-9319 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:39:11.950353+05:30
%A Ibrahim Adeyanju
%T Building a Truly Distributed Constraint Solver with JADE
%J International Journal of Computer Applications
%@ 0975-8887
%V 46
%N 8
%P 1-7
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Real life problems such as scheduling meeting between people at different locations can be modelled as distributed Constraint Satisfaction Problems (CSPs). Suitable and satisfactory solutions can then be found using constraint satisfaction algorithms which can be exhaustive (backtracking) or otherwise (local search). However, most research in this area tested their algorithms by simulation on a single PC with a single program entry point. The main contribution of our work is the design and implementation of a truly distributed constraint solver based on a local search algorithm using Java Agent DEvelopment framework (JADE) to enable communication between agents on different machines. Particularly, we discuss design and implementation issues related to truly distributed constraint solver which might not be critical when simulated on a single machine. Evaluation results indicate that our truly distributed constraint solver works well within the observed limitations when tested with various distributed CSPs. Our application can also incorporate any constraint solving algorithm with little modifications.

References
  1. Dechter R. Constraint Processing. San Francisco, CA: Morgan Kaufmann; 2003.
  2. Makoto Y, Edmund H D, Toru I, Kazuhiro K. The Distributed Constraint Satisfaction Problem: Formalization and Algorithms. IEEE TKDE. 1998; 10(5): 673-685.
  3. Pragnesh J M, Hyuckchul J, Milind T, Wei-Min S, Shriniwas K. Dynamic Distributed Resource Allocation: A Distributed Constraint Satisfaction Approach. In Proceedings of CP'01. Springer, London; 2001: 685-700.
  4. Lamma E, Mello P, Milano M. A distributed constraint-based scheduler. Artificial Intelligence in Engineering. 1997; 11(1): 91-105.
  5. Dechter R, Enhancement schemes for constraint processing: Backjumping, learning, cutset decomposition. Artificial Intelligence. 1990; 41(3): 273-312.
  6. Chen X, van Beek P. Conflict-Directed Backjumping Revisited. JAIR. 2001; 14: 53-81.
  7. Makoto Yokoo. Asynchronous Weak-commitment Search for Solving Distributed Constraint Satisfaction Problems. In Proceedings of CP'95. Springer, London; 1995:88-102.
  8. Meisels A, Zivan R. Asynchronous Forward-checking for DisCSPs. Constraints. 2007; 12(1): 131-150.
  9. Ioannidis Y E, Wong E. Query optimization by simulated annealing. In Proceedings of the international conference on Management of data. ACM, NY; 1987: 9-22.
  10. Wong D F. On simulated annealing in EDA. In Proceedings of the International Symposium on Physical Design. ACM, NY; 2012: 63-64.
  11. Morris P. The breakout method for escaping from local minima. In: Proceedings of the National Conference on Artificial Intelligence. 1993: 40-45.
  12. Glover F, Laguna M. Tabu Search. Kluwer Academic Publishers, Norwell, MA, USA; 1997.
  13. Hirayama K, Yokoo M. The distributed breakout algorithms. Artificial Intelligence. 2005; 161(1): 89-115.
  14. Zhang W, Wittenburg L. Distributed breakout revisited. In Proceedings of the national conference on Artificial intelligence. 2002: 352-357. Basharu M B. Modifying Landscapes with Penalties in Iterative Improvements for Solving Distributed Constraints Satisfaction Problems. [PhD Thesis]. Aberdeen: Robert Gordon University; 2006.
  15. Birrell A D, Nelson B J. Implementing remote procedure calls. ACM Transaction on Computer Systems. 1984; 2(1): 39-59.
  16. Gomes-Soares P. On remote procedure call. In Proceedings of the conference of the Centre for Advanced Studies on Collaborative research. IBM Press. 1992; 2: 215-267.
  17. Don W. Browning. . Net Remoting. Manning Publications Co. , Greenwich, CT, USA; 2002.
  18. Ingo Rammer. Advanced . Net Remoting. Apress, Berkely, CA, USA; 2002.
  19. Maassen J, Van-Nieuwpoort R, Veldema R, Bal H, Kielmann T, Jacobs C, Hofman R. Efficient Java RMI for parallel programming. ACM Transaction on Programming Languages and Systems. 2001; 23(6): 747-775.
  20. Waldo J. Remote Procedure Calls and Java RMI. IEEE Concurrency. 1998; 6(3): 5-7.
  21. Bethea W L. Adding parametric polymorphism to the common object request broker architecture (CORBA). In Addendum to the proceedings of OOPSLA '00. ACM, NY; 2000: 119-120.
  22. Felber P. ; Guerraoui R. Programming with object groups in CORBA. IEEE Concurrency. 2000; 8(1): 48-58.
  23. Albuquerque R L, Hubner J F, de Paula G, Sichman J S, Ramalho G. KSACI: A Handheld Device Infrastructure for Agents Communication. In Proceedings of the International Workshop on Intelligent Agents. Springer, London; 2001: 423-435.
  24. Labrou Y, Finin T, Peng Y. Agent Communication Languages: The Current Landscape. IEEE Intelligent Systems. 1999; 14(2): 45-52
  25. Bellifemine F, Caire G, Greenwood D. Developing multi-agent systems with JADE. Chichester: John Wiley & Sons; 2007.
  26. Bellifemine, F, Rimassa, G, Poggi, A. JADE - A FIPA compliant Agent Framework. In Proceedings of the International Conference and Exhibition on the Practical Application of Intelligent Agents and Multi-Agents. London, 1999.
  27. Caire G. JADE Tutorial- Jade Programming for Beginners. Torino, Italy: Telecom Italia Laboratory (TILAB); 2003. Available from: http://jade. tilab. com/
  28. Lee D. SIDCOT: A Smart Interface for Constraint Programming. [Unpublished BSc. Thesis]. Aberdeen: Robert Gordon University; 2006
Index Terms

Computer Science
Information Sciences

Keywords

Constraint Satisfaction Jade Dispel Multi-agent Systems