Distributed Monitoring of Concurrent and Asynchronous Systems
Developing applications over a distributed and asynchronous architecture without the need for synchronization services is going to become a central track for distributed computing. This research track will be central for the domain of autonomic computing and self-management. Distributed constraint solving, distributed observation, and distributed optimization, are instances of such applications. This paper is about distributed observation: we investigate the problem of distributed monitoring of concurrent and asynchronous systems, with application to distributed fault management in telecommunications networks.
Our approach combines two techniques: compositional unfoldings to handle concurrency properly, and a variant of graphical algorithms and belief propagation, originating from statistics and information theory.
Keywordsasynchronous concurrent distributed unfoldings event structures belief propagation fault diagnosis fault management
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- 1.extended version, available as IRISA report No 1540, http://www.irisa.fr/bibli/publi/pi/2003/1540/1540.html
- 2.Aghasaryan, A., Dousson, C., Fabre, E., Pencolé, Y., Osmani, A.: Modeling Fault Propagation in Telecommunications Networks for Diagnosis Purposes. XVIII World Telecommunications Congress September 22–27, 2002 – Paris, France (2002), Available: http://www.irisa.fr/sigma2/benveniste/pub/topic_distribdiag.html
- 3.Benveniste, A., Fabre, E., Jard, C., Haar, S.: Diagnosis of asynchronous discrete event systems, a net unfolding approach. IEEE Trans. on Automatic Control, 48(5) (May 2003), Preliminary version available from http://www.irisa.fr/sigma2/benveniste/pub/IEEE_TAC_AsDiag_2003.html
- 4.Benveniste, A., Haar, S., Fabre, E.: Markov Nets: probabilistic Models for Distributed and Concurrent Systems. INRIA Report 4235 (2001), available electronically at http://www.inria.fr/rrrt/rr-4754.html
- 11.Fabre, E., Benveniste, A., Jard, C.: Distributed diagnosis for large discrete event dynamic systems. In: Proc of the IFAC congress (July 2002)Google Scholar
- 12.Fabre, E.: Compositional models of distributed and asynchronous dynamical systems. In: Proc of the 2002 IEEE Conf. on Decision and Control, Las Vegas, December 1-6 (2002)Google Scholar
- 13.Fabre, E.: Monitoring distributed systems with distributed algorithms. In: Proc of the 2002 IEEE Conf. on Decision and Control, Las Vegas, December 2002, pp. 411–416 (2002)Google Scholar
- 14.Fabre, E.: Distributed diagnosis for large discrete event dynamic systems (in preparation)Google Scholar
- 15.Fabre, E.: Convergence of the turbo algorithm for systems defined by local constraints. IRISA Res. Rep. 1510 (2003)Google Scholar
- 16.Goodwin, G.C., Sin, K.S.: Adaptive Filtrering, Prediction, and Control. Prentice-Hall, Upper Sadle River (1984)Google Scholar
- 18.Lamport, L., Lynch, N.: Distributed Computing: Models and Methods. In: van Leeuwen, J. (ed.) Handbook of Theoretical Computer Science. Formal Models and Semantics, vol. B, pp. 1157–1199. Elsevier, Amsterdam (1990)Google Scholar
- 19.Lauritzen, S.L.: Graphical Models. Oxford Statistical Science Series, vol. 17. Oxford University Press, Oxford (1996)Google Scholar