CONCUR 2003 - Concurrency Theory: 14th International by Albert Benveniste, Stefan Haar, Eric Fabre, Claude Jard
By Albert Benveniste, Stefan Haar, Eric Fabre, Claude Jard (auth.), Roberto Amadio, Denis Lugiez (eds.)
This publication constitutes the refereed lawsuits of the 14th overseas convention on Concurrency conception, CONCUR 2003, held in Marseille, France in September 2003.
The 29 revised complete papers offered including four invited papers have been conscientiously reviewed and chosen from 107 submissions. The papers are geared up in topical sections on partial orders and asynchronous platforms, approach algebras, video games, limitless structures, probabilistic automata, version checking, version checking and HMSC, safeguard, mobility, compositional equipment and genuine time, and probabilistic models.
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Additional info for CONCUR 2003 - Concurrency Theory: 14th International Conference, Marseille, France, September 3-5, 2003. Proceedings
2002, Las Vegas, 2002. 13. E. Fabre. Monitoring distributed systems with distributed algorithms. In Proc of the 2002 IEEE Conf. on Decision and Control, 411–416, Dec. 2002, Las Vegas, 2002. 14. E. Fabre. Distributed diagnosis for large discrete event dynamic systems. In preparation. 15. E. Fabre. Convergence of the turbo algorithm for systems deﬁned by local constraints. IRISA Res. Rep. 1510, 2003. 16. C. S. Sin. Adaptive Filtrering, Prediction, and Control. J. 1984. 17. S. Haar. Probabilistic Cluster Unfoldings.
Note that N(i) contains i. , a set of Ci , i ∈ I such that C= Ci , (14) i∈I and it aims at computing ΠPi (C), for i ∈ I, in a chaotic way. In the following algorithm, each site i maintains and updates, for each neighbour j, a message Mi,j toward j. Thus there are two messages per edge (i, j) of GI , one in each direction: Algorithm 1 1. Initialization: for each edge (i, j) ∈ GI : Mi,j = ΠPi ∩Pj (1). (15) 2. Chaotic iteration: until stabilization, select an edge (i, j) ∈ GI , and update: Mi,j := ΠPi ∩Pj Ci ∧ k∈N(i)\j Mk,i .
Probabilistic aspects are also of interest, to resolve nondeterminism by performing maximum likelihood diagnosis. The papers [4, 17] propose two possible mathematical frameworks for this, and a third one is in preparation. References 1. html 2. A. Aghasaryan, C. Dousson, E. Fabre, Y. Pencol´e, A. Osmani. Modeling Fault Propagation in Telecommunications Networks for Diagnosis Purposes. XVIII World Telecommunications Congress 22–27 September 2002 – Paris, France. html 3. A. Benveniste, E. Fabre, C.