Abstract
In this chapter a novel approach to coordination in self-organising systems is described, which rethinks the basis of chemically inspired coordination, from both the engineering standpoint of coordination laws and primitives design, and from the scientific standpoint of relative linguistic expressiveness. Accordingly, first of all state of art literature regarding nature-inspired coordination is reviewed (Sects. 3.1 and 3.2), then the well-known local versus global issue in self-organising systems is dealt with by engineering coordination laws as artificial chemical reactions with custom kinetic rates (Sect. 3.3). After this, the impact of uniform coordination primitives on self-organising systems is discussed, experiments on their applicability are reported, and their formal semantics is defined (Sect. 3.4).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Actually, the BTS model is an hybrid CTMC/DTMC model, since instantaneous transitions are allowed; please, refer to [49] for a thorough explanation.
- 2.
FP7-ICT-2009.8.5: Self-awareness in Autonomic Systems.
- 3.
Except repulsion/attraction, that has been left out since it can be engineered on top of diffusion.
- 4.
- 5.
How the destination compartment is chosen is not relevant here.
References
Alves, R., Antunes, F., Salvador, A.: Tools for kinetic modeling of biochemical networks. Nat. Biotechnol. 24(6), 667–672 (2006). doi:10.1038/nbt0606-667
Beal, J., Bachrach, J.: Infrastructure for engineered emergence on sensor/actuator networks. Int. Syst. IEEE 21(2), 10–19 (2006)
de Boer, F.S., Palamidessi, C.: Embedding as a tool for language comparison. Inf. Comput. 108(1), 128–157 (1994). doi:10.1006/inco.1994.1004
Bravetti, M.: Expressing priorities and external probabilities in process algebra via mixed open/closed systems. Electron. Notes Theor. Comput. Sci. 194(2), 31–57 (2008). doi:10.1016/j.entcs.2007.11.003
Bravetti, M., Gorrieri, R., Lucchi, R., Zavattaro, G.: Quantitative information in the tuple space coordination model. Theoret. Comput. Sci. 346(1), 28–57 (2005). doi:10.1016/j.tcs.2005.08.004
Busi, N., Gorrieri, R., Zavattaro, G.: On the expressiveness of linda coordination primitives. Inf. Comput. 156(1), 90–121 (2000)
Cabri, G., Leonardi, L., Zambonelli, F.: MARS: A programmable coordination architecture for mobile agents. IEEE Int. Comput. 4(4), 26–35 (2000). doi:10.1109/4236.865084
Cardelli, L.: On process rate semantics. Theor. Comput. Sci. 391(3), 190–215 (2008)
Casadei, M., Viroli, M.: Toward approximate stochastic model checking of computational fields for pervasive computing systems. In: Pitt, J. (ed.) Self-Adaptive and Self-Organizing Systems Workshops (SASOW), pp. 199–204. IEEE CS (2013). doi:10.1109/SASOW.2012.42. 2012 IEEE Sixth International Conference (SASOW 2012), Lyon, France, 10-14 Sep. 2012. Proceedings
Casadei, M., Viroli, M., Gardelli, L.: On the collective sort problem for distributed tuple spaces. Sci. Comput. Program. 74(9), 702–722 (2009). doi:10.1016/j.scico.2008.09.018
Ciocchetta, F., Hillston, J.: Bio-PEPA: A framework for the modelling and analysis of biological systems. Theor. Comput. Sci. 410(33–34), 3065–3084 (2009). doi:10.1016/j.tcs.2009.02.037. Concurrent Systems Biology: To Nadia Busi (1968–2007)
De Nicola, R., Latella, D., Katoen, J.P., Massink, M.: StoKlaim: A stochastic extension of Klaim. Tech. Rep. 2006-TR-01, Istituto di Scienza e Tecnologie dell’Informazione “Alessandro Faedo” (ISTI) (2006). http://www1.isti.cnr.it/~Latella/StoKlaim.pdf
De Wolf, T., Holvoet, T.: Design patterns for decentralised coordination in self-organising emergent systems. In: Engineering Self-organising Systems, pp. 28–49. Springer (2007)
Denti, E., Natali, A., Omicini, A.: Programmable coordination media. In: Garlan, D., Le Métayer, D. (eds.) Coordination Languages and Models, LNCS, vol. 1282, pp. 274–288. Springer (1997). doi:10.1007/3-540-63383-9
Denti, E., Natali, A., Omicini, A.: On the expressive power of a language for programming coordination media. In: 1998 ACM Symposium on Applied Computing (SAC’98), pp. 169–177. ACM, Atlanta, GA, USA (1998)
Di Pierro, A., Hankin, C., Wiklicky, H.: Probabilistic KLAIM. In: De Nicola, R., Ferrari, G.L., Meredith, G. (eds.) Coordination Models and Languages, LNCS, vol. 2949, pp. 119–134. Springer Berlin/Heidelberg (2004). doi:10.1007/978-3-540-24634-3
Di Pierro, A., Hankin, C., Wiklicky, H.: Probabilistic Linda-based coordination languages. In: de Boer, F.S., Bonsangue, M.M., Graf, S., de Roever, W.P. (eds.) 3rd International Conference on Formal Methods for Components and Objects (FMCO’04), LNCS, vol. 3657, pp. 120–140. Springer, Berlin, Heidelberg (2005). doi:10.1007/11561163
Dorigo, M., Birattari, M.: Ant colony optimization. In: Sammut, C., Webb, G. (eds.) Encyclopedia of Machine Learning, pp. 36–39. Springer US (2010). doi:10.1007/978-0-387-30164-8
Fernandez-Marquez, J.L., Di Marzo Serugendo, G., Arcos, J.L.: Infrastructureless spatial storage algorithms. ACM Trans. Auton. Adapt. Syst. (TAAS) 6(2), 15 (2011)
Fernandez-Marquez, J.L., Di Marzo Serugendo, G., Montagna, S., Viroli, M., Arcos, J.L.: Description and composition of bio-inspired design patterns: a complete overview. Nat. Comput. 12(1), 43–67 (2013). doi:10.1007/s11047-012-9324-y
Fernandez-Marquez, J.L., Serugendo, G.D.M., Montagna, S.: Bio-core: Bio-inspired self-organising mechanisms core. Bio-Inspired Models of Networks. Information, and Computing Systems, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 103, pp. 59–72. Springer, Berlin, Heidelberg (2012)
Gardelli, L., Viroli, M., Casadei, M., Omicini, A.: Designing self-organising MAS environments: The collective sort case. In: D. Weyns, H.V.D. Parunak, F. Michel (eds.) Environments for MultiAgent Systems III, LNAI, vol. 4389, pp. 254–271. Springer (2007). doi:10.1007/978-3-540-71103-2
Gardelli, L., Viroli, M., Omicini, A.: On the role of simulations in engineering self-organising MAS: The case of an intrusion detection system in TuCSoN. In: Brueckner, S.A., Di Marzo Serugendo, G., Hales, D., Zambonelli, F. (eds.) Engineering Self-Organising Systems, LNAI, vol. 3910, pp. 153–168. Springer, Berlin, Heidelberg (2006). doi:10.1007/11734697. 3rd International Workshop (ESOA 2005), Utrecht, The Netherlands, 26 July 2005. Revised Selected Papers
Gardelli, L., Viroli, M., Omicini, A.: Combining simulation and formal tools for developing self-organizing MAS. In: Uhrmacher, A.M., Weyns, D. (eds.) Multi-Agent Systems: Simulation and Applications, Computational Analysis, Synthesis, and Design of Dynamic Systems, Chap. 5, pp. 133–165. CRC Press (2009). http://crcpress.com/product/isbn/9781420070231
Gelernter, D.: Generative communication in Linda. ACM Trans. Program. Lang. Syst. 7(1), 80–112 (1985). doi:10.1145/2363.2433
Gillespie, D.T.: Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem. 81(25), 2340–2361 (1977). doi:10.1021/j100540a008
Gilmore, S., Hillston, J.: The PEPA workbench: A tool to support a process algebra-based approach to performance modelling. In: Haring, G., Kotsis, G. (eds.) Computer Performance Evaluation Modelling Techniques and Tools, Lecture Notes in Computer Science, vol. 794, pp. 353–368. Springer, Berlin, Heidelberg (1994). doi:10.1007/3-540-58021-2
Hermanns, H.: Interactive Markov Chains: And the Quest for Quantified Quality. Springer (2002)
Mamei, M., Menezes, R., Tolksdorf, R., Zambonelli, F.: Case studies for self-organization in computer science. J. Syst. Architect. 52(8), 443–460 (2006)
Mariani, S.: On the “local-to-global” issue in self-organisation: Chemical reactions with custom kinetic rates. In: Eighth IEEE International Conference on Self-adaptive and Self-organizing Systems Workshops, SASOW 2014, Eighth IEEE International Conference on Self-Adaptive and Self-organizing Systems Workshops, SASOW 2014, pp. 61–67. IEEE, London, UK (2014). doi:10.1109/SASOW.2014.14. Best student paper award
Mariani, S., Omicini, A.: Probabilistic embedding: Experiments with tuple-based probabilistic languages. In: 28th ACM Symposium on Applied Computing (SAC 2013), pp. 1380–1382. Coimbra, Portugal (2013). doi:10.1145/2480362.2480621. Poster Paper
Mariani, S., Omicini, A.: Probabilistic modular embedding for stochastic coordinated systems. In: Julien, C., De Nicola, R. (eds.) Coordination Models and Languages, LNCS, vol. 7890, pp. 151–165. Springer (2013). doi:10.1007/978-3-642-38493-6. 15th International Conference (COORDINATION 2013), Florence, Italy, 3–6 June 2013. Proceedings
Mariani, S., Omicini, A.: Coordination mechanisms for the modelling and simulation of stochastic systems: The case of uniform primitives. SCS M&S Magazine IV, 6–25 (2014). Special Issue on “Agents and Multi-Agent Systems: From Objects to Agents”
Merelli, E., Armano, G., Cannata, N., Corradini, F., d’Inverno, M., Doms, A., Lord, P., Martin, A., Milanesi, L., Möller, S., Schroeder, M., Luck, M.: Agents in bioinformatics, computational and systems biology. Briefings Bioinf. 8(1), 45–59 (2007). doi:10.1093/bib/bbl014
Minsky, N.H., Ungureanu, V.: Law-Governed interaction: A coordination and control mechanism for heterogeneous distributed systems. ACM Trans. Soft. Eng. Methodol. (TOSEM) 9(3), 273–305 (2000). doi:10.1145/352591.352592
Nagpal, R.: A catalog of biologically-inspired primitives for engineering self-organization. In: Engineering Self-organising Systems, pp. 53–62. Springer (2004)
Nardini, E., Omicini, A., Viroli, M.: Description spaces with fuzziness. In: Palakal, M.J., Hung, C.C., Chu, W., Wong, W.E. (eds.) 26th Annual ACM Symposium on Applied Computing (SAC 2011), vol. II: Artificial Intelligence & Agents, Information Systems, and Software Development, pp. 869–876. ACM, Tunghai University, TaiChung, Taiwan (2011). doi:10.1145/1982185.1982375
Omicini, A.: Formal ReSpecT in the A&A perspective. Electron. Notes Theor. Comput. Sci. 175(2), 97–117 (2007). doi:10.1016/j.entcs.2007.03.006
Omicini, A.: Nature-inspired coordination for complex distributed systems. In: Intelligent Distributed Computing VI, pp. 1–6. Springer (2013)
Omicini, A.: Nature-inspired coordination models: Current status, future trends. ISRN Softw. Eng. 2013 (2013). doi:10.1155/2013/384903
Omicini, A., Denti, E.: Formal ReSpecT. Electron. Notes Theor. Comput. Sci. 48, 179–196 (2001). doi:10.1016/S1571-0661(04)00156-2
Omicini, A., Denti, E.: From tuple spaces to tuple centres. Sci. Comput. Program. 41(3), 277–294 (2001). doi:10.1016/S0167-6423(01)00011-9
Omicini, A., Viroli, M.: Coordination models and languages: From parallel computing to self-organisation. Knowl. Eng. Rev. 26(1), 53–59 (2011). doi:10.1017/S026988891000041X
Omicini, A., Zambonelli, F.: Coordination for Internet application development. Auton. Agent. Multi-Agent Syst. 2(3), 251–269 (1999). doi:10.1023/A:1010060322135
Parunak, H.V.D., Brueckner, S., Sauter, J.: Digital pheromone mechanisms for coordination of unmanned vehicles. In: Castelfranchi, C., Johnson, W.L. (eds.) 1st International Joint Conference on Autonomous Agents and Multiagent systems, vol. 1, pp. 449–450. ACM, New York, NY, USA (2002). http://dx.doi.org/10.1145/544741.544843
Pérez, P.G., Omicini, A., Sbaraglia, M.: A biochemically inspired coordination-based model for simulating intracellular signalling pathways. J. Simul. 7(3), 216–226 (2013)
Shapiro, E.: Separating concurrent languages with categories of language embeddings. In: 23rd Annual ACM Symposium on Theory of Computing (STOC’91), pp. 198–208. ACM, New York, NY, USA (1991). doi:10.1145/103418.103423
Tchao, A.E., Risoldi, M., Di Marzo Serugendo, G.: Modeling self-* systems using chemically-inspired composable patterns. In: Self-Adaptive and Self-organizing Systems (SASO), 2011 Fifth IEEE International Conference on, pp. 109–118 (2011). doi:10.1109/SASO.2011.22
Viroli, M., Casadei, M.: Biochemical tuple spaces for self-organising coordination. In: Field, J., Vasconcelos, V.T. (eds.) Coordination Languages and Models, LNCS, vol. 5521, pp. 143–162. Springer, Lisbon, Portugal (2009). doi:10.1007/978-3-642-02053-7
Viroli, M., Casadei, M., Montagna, S., Zambonelli, F.: Spatial coordination of pervasive services through chemical-inspired tuple spaces. ACM Trans. Auton. Adapt. Syst. 6(2), 14:1–14:24 (2011). doi:10.1145/1968513.1968517
Viroli, M., Casadei, M., Omicini, A.: A framework for modelling and implementing self-organising coordination. In: Shin, S.Y., Ossowski, S., Menezes, R., Viroli, M. (eds.) 24th Annual ACM Symposium on Applied Computing (SAC 2009), vol. III, pp. 1353–1360. ACM, Honolulu, Hawai’i, USA (2009). doi:10.1145/1529282.1529585
Wegner, P.: Why interaction is more powerful than algorithms. Commun. ACM 40(5), 80–91 (1997). doi:10.1145/253769.253801
Wegner, P., Goldin, D.: Computation beyond Turing machines. Commun. ACM 46(4), 100–102 (2003). doi:10.1145/641205.641235
Zambonelli, F., Omicini, A., Anzengruber, B., Castelli, G., DeAngelis, F.L., Di Marzo Serugendo, G., Dobson, S., Fernandez-Marquez, J.L., Ferscha, A., Mamei, M., Mariani, S., Ye, J.: Developing pervasive multi-agent systems with nature-inspired coordination. Pervasive Mob. Comput. 17, 236–252 (2015). doi:10.1016/j.pmcj.2014.12.002. Special Issue “10 years of Pervasive Computing” In Honor of Chatschik Bisdikian
Zambonelli, F., Viroli, M.: Architecture and metaphors for eternally adaptive service ecosystems. In: Intelligent Distributed Computing, Systems and Applications, Studies in Computational Intelligence, vol. 162/2008, pp. 23–32. Springer (2008). doi:10.1007/978-3-540-85257-5. 2nd International Symposium on Intelligent Distributed Computing (IDC 2008), Catania, Italy, 18–19 Sep. 2008. Proceedings
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this chapter
Cite this chapter
Mariani, S. (2016). Coordination of Self-organising Systems. In: Coordination of Complex Sociotechnical Systems. Artificial Intelligence: Foundations, Theory, and Algorithms. Springer, Cham. https://doi.org/10.1007/978-3-319-47109-9_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-47109-9_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-47108-2
Online ISBN: 978-3-319-47109-9
eBook Packages: Computer ScienceComputer Science (R0)