8,799 research outputs found

    Properties of Distributed Time Arc Petri Nets

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    In recent work we started a research on a distributed-timed extension of Petri nets where time parameters are associated with tokens and arcs carry constraints that qualify the age of tokens required for enabling. This formalism enables to model e.g. hardware architectures like GALS. We give a formal definition of process semantics for our model and investigate several properties of local versus global timing: expressiveness, reachability and coverability

    A case study in model-driven synthetic biology

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    We report on a case study in synthetic biology, demonstrating the modeldriven design of a self-powering electrochemical biosensor. An essential result of the design process is a general template of a biosensor, which can be instantiated to be adapted to specific pollutants. This template represents a gene expression network extended by metabolic activity. We illustrate the model-based analysis of this template using qualitative, stochastic and continuous Petri nets and related analysis techniques, contributing to a reliable and robust design

    Towards a Notion of Distributed Time for Petri Nets

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    We set the ground for research on a timed extension of Petri nets where time parameters are associated with tokens and arcs carry constraints that qualify the age of tokens required for enabling. The novelty is that, rather than a single global clock, we use a set of unrelated clocks --- possibly one per place --- allowing a local timing as well as distributed time synchronisation. We give a formal definition of the model and investigate properties of local versus global timing, including decidability issues and notions of processes of the respective models

    A Petri-Net Based Approach to Measure the Learnability of Interactive Systems

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    We propose an approach to measure the learnability of an interactive system. Our approach relies on recording in a user log all the user actions that take place during a run of the system and on replaying them over one or more interaction models of the system. Each interaction model describes the expected way of executing a relevant task provided by the system. The proposed approach is able to identify deviations between the interaction models and the user log and to assess the weight of such deviations through a fitness value, which estimates how much a log adheres to the models. Our thesis is that by measuring the rate of such a fitness value for subsequent executions of the system we can not only understand if the system is learnable with respect to its relevant tasks, but also to identify potential learning issues. Ā© 2016 Copyright held by the owner/author(s)

    Performance modeling of e-procurement workflow using Generalised Stochastic Petri net (GSPN)

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    This paper proposes a Generalised Stochastic Petri net (GSPN) model representing a generic e-procurement workflow process. The model displays the dynamic behaviour of the system and shows the inter relationship of process activities. An analysis based on matrix equation approach enabled users to analyse the critical system's states, and thus justify the process performance. The results obtained allow users for better decision making in improving e-procurement workflow performance

    The derivation of performance expressions for communication protocols from timed Petri net models

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    Petri Net models have been extended in a variety of ways and have been used to prove the correctness and evaluate the performance of communication protocols. Several extensions have been proposed to model time. This work uses a form of Timed Petri Nets and presents a technique for symbolically deriving expressions which describe system performance. Unlike past work on performance evaluation of Petri Nets which assumes a priori knowledge of specific time delays, the technique presented here applies to a wide range of time delays so long as the delays satisfy a set of timing constraints. The technique is demonstrated using a simple communication protocol
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