Detecting Non-Ergodic Simulation Models of Logistics Networks

Bause, Falko; Kriege, Jan

doi:10.4108/valuetools.2007.1817

Cited by 4 publications

(10 citation statements)

References 13 publications

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“…In particular, we will try to apply techniques such as Petri nets [2] and model checking [6] to formally understand and describe the possible dynamics of the system.…”

Section: Conclusion and Research Directionsmentioning

confidence: 99%

Behavior Predictability Despite Non-Determinism in the SAPERE Ecosystem

Castelli

Mamei

Rosi

et al. 2012

2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems Workshops

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How can we have confidence that self organizing systems actually do what we expect them to? In this position paper we overview some mechanisms at the basis of controlling and predicting the behavior of autonomous and self-organizing systems despite components' autonomy and non-deterministic behavior. In particular we focus the analysis on the SAPERE ecosystem as an exemplary model to frame the discussion. We identify three main directions with which to gain confidence on the overall system behavior: (i) confidence from layering, (ii) confidence from large numbers, (iii) confidence form the structure and dynamics of the state space. In the paper we describe this ideas and their implication in the design of self organizing applications.

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“…In particular, we will try to apply techniques such as Petri nets [2] and model checking [6] to formally understand and describe the possible dynamics of the system.…”

Section: Conclusion and Research Directionsmentioning

confidence: 99%

Behavior Predictability Despite Non-Determinism in the SAPERE Ecosystem

Castelli

Mamei

Rosi

et al. 2012

2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems Workshops

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“…In the ProC/B toolset PN techniques [19] are used to analyze functional and non-functional properties. Classical PN techniques allow one to analyze properties such as deadlocks or liveness of a system and recently we developed an additional PNbased technique to detect non-ergodic models [20]. All of these, usually undesired, properties of a model are often difficult to detect with simulation.…”

Section: Non-simulative Analysismentioning

confidence: 99%

A Simulation Environment for Hierarchical Process Chains Based on OMNeT++

et al. 2009

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OMNeT++ is a discrete event simulation environment primarily designed for communication networks. In this paper we present an approach to enable OMNeT++ to simulate complex hierarchical process chains. Process chains are a common modeling paradigm in the logistics area for the analysis and optimization of large process chains and have been intensely used in many practical applications. Their evaluation is supported by the ProC/B toolset, a collection of software tools for modeling, analysis, validation and optimization of process chains. Here we describe how OMNeT++ has been integrated as a new simulation engine into the toolset. The integration has to get over some core problems to allow a smooth interaction between OMNeT++ and the other tools: In particular, the OMNeT++ model description of the logistics network should be kept manageable, it should reflect the entire model structure and non-standard performance figures, being relevant for an economic evaluation, should be ascertainable in order to satisfy the specific needs of the application area. The paper highlights the main steps of the automatic transformation of a hierarchical process chain model into a hierarchical model in OMNeT++. Furthermore, we show how the transformation has been validated and how detailed performance figures can be evaluated with OMNeT++.

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“…The philosophy of ProC/B is to describe system behaviour by process chains and system structure by functional units. Figure 2 and Figure 3 present a typical example of a ProC/B model [3]. The model is hierarchical and represents a freight village.…”

Section: Proc/bmentioning

confidence: 99%

“…In the course of the Collaborative Research Centre 559 "Modelling of Large Logistics Networks" (CRC 559; [1,2]) we made the experience that during the construction of a simulation model several interim versions of the model do not correctly reflect the system behaviour. We found that various discrepancies between the system and the model can be discovered by investigating functional properties [1,3,4]. An example is the occurrence of (partial) deadlocks in the simulation model which do not appear in the real system.…”

Section: Introductionmentioning

confidence: 99%

“…Here we will look behind the scenes. The detection of functional deficits in ProC/B models is done by mapping those models to Petri nets (PN) keeping essential characteristics [3,4]. Petri nets [10] are distinguished by very efficient algorithms for checking functional properties and we show how these algorithms can be employed for the validation of ProC/B simulation models.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Validation of Process-based Simulation Models

Bause¹,

Kriege²,

Vastag³

2009

SNE

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Validation is often time-consuming for simulation models of complex systems especially if failures indicating discrepancies between the system and the corresponding model occur rarely. Some failure types can be detected on the basis of the model's structure employing corresponding efficient techniques. In this paper we present some techniques used in the Collaborative Research Centre 559 ("Modelling of Large Logistics Networks") for the validation of process-based simulation models. These techniques are based on efficient algorithms from the Petri net area, but details are completely hidden from the end user by means of a corresponding toolset. Here we present some internals showing how specific aspects of simulation models can be validated efficiently.

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Detecting Non-Ergodic Simulation Models of Logistics Networks

Cited by 4 publications

References 13 publications

Behavior Predictability Despite Non-Determinism in the SAPERE Ecosystem

Behavior Predictability Despite Non-Determinism in the SAPERE Ecosystem

A Simulation Environment for Hierarchical Process Chains Based on OMNeT++

Efficient Validation of Process-based Simulation Models

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