Mirko Viroli
Andrea Omicini
ABSTRACT
Research fields like pervasive computing are showing that the interactions between components in large-scale, mobile, and open systems are highly affected by unpredictability: self-organising techniques are increasingly adopted within infrastructures aimed at managing such interactions in a robust and adaptive way. Accordingly, in this paper we discuss the framework of self-organising coordination: coordination media spread over the network are in charge of managing interactions with each other and with agents solely according to local criteria, making interesting and fruitful global properties of the resulting system appearing by emergence---probability and timing typically playing a crucial role. We show that the TuCSoN coordination infrastructure can be used as a general platform for enacting self-organising coordination; we put it to test on two cases: an inter-space application of adaptive tuple clustering, and a intra-space application of chemical-like coordination reactions.
- F. Arbab. Reo: a channel-based coordination model for component composition. Mathematical Structures in Computer Science, 14(3): 329--366, 2004. Google Scholar
Digital Library
- G. Berry and G. Boudol. The chemical abstract machine. Theoretical Computer Science, 96(1): 217--248, Apr. 1992. Google ScholarDigital Library
- E. Bonabeau, M. Dorigo, and G. Theraulaz. Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, Inc., 1999. Google ScholarDigital Library
- J.-P. Bonâtre and D. Le Métayer. Gamma and the chemical reaction model: Ten years after. In Coordination Programming, pages 3--41. Imperial College Press London, UK, 1996. Google ScholarDigital Library
- M. Bravetti, R. Gorrieri, R. Lucchi, and G. Zavattaro. Probabilistic and prioritized data retrieval in the Linda coordination model. In Coordination Models and Languages, volume 2949 of LNCS, pages 55--70. Springer, 2004.Google Scholar
- M. Bravetti, R. Gorrieri, R. Lucchi, and G. Zavattaro. Quantitative information in the tuple space coordination model. Theoretical Computer Science, 346(1): 28--57, 2005. Google ScholarDigital Library
- S. Camazine, J.-L. Deneubourg, N. R. Franks, J. Sneyd, G. Theraulaz, and E. Bonabeau. Self-Organization in Biological Systems. Princeton University Press, Princeton, NJ, USA, 2001. Google ScholarDigital Library
- M. Casadei, L. Gardelli, and M. Viroli. Simulating emergent properties of coordination in maude: the collective sort case. Electronic Notes in Theoretical Computer Science, 175(2): 59--80, June 2007. Google ScholarDigital Library
- M. Casadei, A. Omicini, and M. Viroli. Prototyping A&A ReSpecT in Maude. Electronic Notes in Theoretical Computer Science, 194(4): 93--109, Apr. 2008. Google ScholarDigital Library
- M. Casadei and M. Viroli. Applying self-organizing coordination to emergent tuple organization in distributed networks. In S. Brueckner, P. Roberson, and U. Bellur, editors, 2nd IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO'08), pages 213--222, Venice, Italy, 20--24 Oct. 2008. IEEE CS. Google ScholarDigital Library
- R. De Nicola, D. Latella, and M. Massink. Formal modeling and quantitative analysis of Klaim-based mobile systems. In 2005 ACM Symposium on Applied Computing (SAC 2005), pages 428--435. ACM Press, 2005. Google ScholarDigital Library
- S. Dobson, S. Denazis, A. Fernández, D. Gaïti, E. Gelenbe, F. Massacci, P. Nixon, F. Saffre, N. Schmidt, and F. Zambonelli. A survey of autonomic communications. ACM Transactions on Autonomous and Adaptive Systems, 1(2): 223--259, 2006. Google ScholarDigital Library
- D. Gelernter. Generative communication in Linda. ACM Transactions on Programming Languages and Systems, 7(1): 80--112, Jan. 1985. Google ScholarDigital Library
- D. T. Gillespie. Exact stochastic simulation of coupled chemical reactions. The Journal of Physical Chemistry, 81(25): 2340--2361, 1977.Google ScholarCross Ref
- O. Holland and C. Melhuis. Stigmergy, self-organization, and sorting in collective robotics. Artificial Life, 5(2): 173--202, 1999. Google ScholarDigital Library
- M. Mamei, R. Menezes, R. Tolksdorf, and F. Zambonelli. Case studies for self-organization in computer science. Journal of Systems Architecture, 52(8--9): 443--460, 2006. Google ScholarDigital Library
- M. Mamei and F. Zambonelli. Programming pervasive and mobile computing applications with the TOTA middleware. In PerCom 2004, pages 263--273. IEEE, Mar. 2004. Google ScholarDigital Library
- R. Menezes and R. Tolksdorf. Adaptiveness in Linda-based coordination models. In Engineering Self-Organising Systems: Nature-Inspired Approaches to Software Engineering, volume 2977 of LNAI, pages 212--232. Springer, 2004.Google Scholar
- J. S. Nicolis, E. Protonotarios, and E. Lianos. Some views on the role of noise in "self"-organizing systems. Biological Cybernetics, 17(4): 183--193, 1975.Google ScholarDigital Library
- A. Omicini and E. Denti. From tuple spaces to tuple centres. Science of Computer Programming, 41(3): 277--294, Nov. 2001.Google ScholarCross Ref
- A. Omicini, A. Ricci, and M. Viroli. Time-aware coordination in ReSpecT. In J.-M. Jacquet and G. P. Picco, editors, Coordination Models and Languages, volume 3454 of LNCS, pages 268--282. Springer-Verlag, Apr. 2005. Google ScholarDigital Library
- A. Omicini, A. Ricci, and M. Viroli. Timed environment for Web agents. Web Intelligence and Agent Systems, 5(2): 161--175, Aug. 2007. Google ScholarDigital Library
- A. Omicini, A. Ricci, and M. Viroli. Artifacts in the A&A meta-model for multi-agent systems. Autonomous Agents and Multi-Agent Systems, 17(3), Dec. 2008. Special Issue on Foundations, Advanced Topics and Industrial Perspectives of Multi-Agent Systems. Google ScholarDigital Library
- H. V. D. Parunak, S. Brueckner, and J. Sauter. Digital pheromone mechanisms for coordination of unmanned vehicles. In 1st International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2002), pages 449--450. ACM Press, 2002. Google ScholarDigital Library
- A. Phillips. The Stochastic Pi Machine (SPiM). http://research.microsoft.com/~aphillip/spim/.Google Scholar
- C. Priami. Stochastic pi-calculus. The Computer Journal, 38(7): 578--589, 1995.Google ScholarCross Ref
- I. Prigogine and I. Steingers. The End of Certainty: Time, Chaos, and the New Laws of Nature. Free Press, 1997.Google Scholar
- F. Zambonelli and H. V. D. Parunak. Towards a paradigm change in computer science and software engineering: A synthesis. The Knowledge Engineering Review, 18(4): 329--342, Dec. 2003. Google ScholarDigital Library
Index Terms
- A framework for modelling and implementing self-organising coordination
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