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EN
Network models aim to explain patterns of empirical relationships based on mechanisms that operate under various principles for establishing and removing links. The principle of preferential attachment forms a basis for the well-known Barabási–Albert model, which describes a stochastic preferential attachment process where newly added nodes tend to connect to the more highly connected ones. Previous work has shown that a wide class of such models are able to recreate power law degree distributions. This paper characterizes the cumulative degree distribution of the Barabási–Albert model as an invariant set and shows that this set is not only a global attractor, but it is also stable in the sense of Lyapunov. Stability in this context means that, for all initial configurations, the cumulative degree distributions of subsequent networks remain, for all time, close to the limit distribution. We use the stability properties of the distribution to design a semi-supervised technique for the problem of anomalous event detection on networks.
EN
This paper considers the problem of diagnosability analysis of discrete event systems modeled by labeled Petri nets (LPNs). We assume that the LPN can be bounded or unbounded with no deadlock after firing any fault transition. Our approach is novel and presents the on-the-fly diagnosability analysis using verifier nets. For a given LPN model, the verifier net and its reachability graph (for a bounded LPN) or coverability graph (for an unbounded LPN) are built on-the-fly and in parallel for diagnosability analysis. As soon as a diagnosability decision is established, the construction is stopped. This approach achieves a compromise between computation limitations due to efficiency and combinatorial explosion and it is useful to implement an engineering approach to the diagnosability analysis of complex systems.
3
Content available Event monitoring of parallel computations
EN
The paper considers the monitoring of parallel computations for detection of abnormal events. It is assumed that computations are organized according to an event model, and monitoring is based on specific test sequences.
PL
Artykuł przedstawia bibliotekę służącą do modelowania układów zdarzeń dyskretnych według koncepcji wyboru działania, opartą na języku CSL. Cechą charakterystyczną rozwiązania jest zastosowanie platformy .NET oraz języka C#. Duża popularność tych technologii sprawia, że budowa modeli jest możliwa już przy minimalnym nakładzie związanym z zapoznaniem się z API samej biblioteki.
EN
The article presents the library used to discrete events systems modeling based on CSL language. The key point of this implementation is involving of .NET platform and C# language. Big popularity of these technologies makes that building of models is possible with minimal effort related to study of library API.
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