74 research outputs found
Confluence reduction for Markov automata
Markov automata are a novel formalism for specifying systems exhibiting nondeterminism, probabilistic choices and Markovian rates. Recently, the process algebra MAPA was introduced to efficiently model such systems. As always, the state space explosion threatens the analysability of the models generated by such specifications. We therefore introduce confluence reduction for Markov automata, a powerful reduction technique to keep these models small. We define the notion of confluence directly on Markov automata, and discuss how to syntactically detect confluence on the MAPA language as well. That way, Markov automata generated by MAPA specifications can be reduced on-the-fly while preserving divergence-sensitive branching bisimulation. Three case studies demonstrate the significance of our approach, with reductions in analysis time up to an order of magnitude
Performance modeling of e-procurement workflow using Generalised Stochastic Petri net (GSPN)
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
An efficient algorithm for the parallel solution of high-dimensional differential equations
The study of high-dimensional differential equations is challenging and
difficult due to the analytical and computational intractability. Here, we
improve the speed of waveform relaxation (WR), a method to simulate
high-dimensional differential-algebraic equations. This new method termed
adaptive waveform relaxation (AWR) is tested on a communication network
example. Further we propose different heuristics for computing graph partitions
tailored to adaptive waveform relaxation. We find that AWR coupled with
appropriate graph partitioning methods provides a speedup by a factor between 3
and 16
Repairing Event Logs Using Timed Process Models
Process mining aims to infer meaningful insights from process-related data and attracted the attention of practitioners, tool-vendors, and researchers in recent years. Traditionally, event logs are assumed to describe the as-is situation. But this is not necessarily the case in environments where logging may be compromised due to manual logging. For example, hospital staff may need to manually enter information regarding the patientâs treatment. As a result, events or timestamps may be missing or incorrect. In this work, we make use of process knowledge captured in process models, and provide a method to repair missing events in the logs. This way, we facilitate analysis of incomplete logs. We realize the repair by combining stochastic Petri nets, alignments, and Bayesian networks. Keywords: process mining; missing data; stochastic Petri nets; Bayesian network
Distributed Markovian Bisimulation Reduction aimed at CSL Model Checking
The verification of quantitative aspects like performance and dependability by means of model checking has become an important and vivid area of research over the past decade.\ud
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An important result of that research is the logic CSL (continuous stochastic logic) and its corresponding model checking algorithms. The evaluation of properties expressed in CSL makes it necessary to solve large systems of linear (differential) equations, usually by means of numerical analysis. Both the inherent time and space complexity of the numerical algorithms make it practically infeasible to model check systems with more than 100 million states, whereas realistic system models may have billions of states.\ud
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To overcome this severe restriction, it is important to be able to replace the original state space with a probabilistically equivalent, but smaller one. The most prominent equivalence relation is bisimulation, for which also a stochastic variant exists (Markovian bisimulation). In many cases, this bisimulation allows for a substantial reduction of the state space size. But, these savings in space come at the cost of an increased time complexity. Therefore in this paper a new distributed signature-based algorithm for the computation of the bisimulation quotient of a given state space is introduced.\ud
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To demonstrate the feasibility of our approach in both a sequential, and more important, in a distributed setting, we have performed a number of case studies
Matrix-geometric solution of infinite stochastic Petri nets
We characterize a class of stochastic Petri nets that can be solved using matrix geometric techniques. Advantages of such on approach are that very efficient mathematical technique become available for practical usage, as well as that the problem of large state spaces can be circumvented. We first characterize the class of stochastic Petri nets of interest by formally defining a number of constraints that have to be fulfilled. We then discuss the matrix geometric solution technique that can be employed and present some boundary conditions on tool support. We illustrate the practical usage of the class of stochastic Petri nets with two examples: a queueing system with delayed service and a model of connection management in ATM network
Modelling and Simulation of Queuing Models through the concept of Petri Nets
In recent years Petri Nets has been in demand due to its visual depiction. Petri Nets are used as an effective method for portraying synchronization, a concurrency between different system activities. In queuing models Petri networks are used to represent distributed modeling of the system and thus evaluate their performance. By specifying suitable stochastic Petri Nets models, the authors concentrate on representing multi-class queuing systems of various queuing disciplines. The key idea is to define SPN models that simulate a given queue discipline 's behavior with some acceptable random choice. Authors have find system queuing with both a single server and multiple servers with load-dependent service rate. Petri networks in the queuing model have enhanced scalability by combining queuing and modeling power expressiveness of 'petri networks.' Examples of application of SPN models to performance evaluation of multiprocessor systems demonstrate the utility and effectiveness of this modeling method. In this paper, authors have made use of Stochastic Petri nets in queuing models to evaluate the performance of the system
Phased mission modelling of systems with maintenance free operating periods using simulated Petri-nets
A common scenario in engineering is that of a system which operates throughout
several sequential and distinct periods of time, during which the modes and
consequences of failure differ from one another. This type of operation is known as a
phased mission, and for the mission to be a success the system must successfully
operate throughout all of the phases. Examples include a rocket launch and an
aeroplane flight. Component or sub-system failures may occur at any time during the
mission, yet not affect the system performance until the phase in which their
condition is critical. This may mean that the transition from one phase to the next is a
critical event that leads to phase and mission failure, with the root cause being a
component failure in a previous phase. A series of phased missions with no
maintenance may be considered as a Maintenance Free Operating Period (MFOP).
This paper describes the use of a Petri net to model the reliability of the MFOP and
phased missions scenario. The model uses a form of Monte-Carlo simulation to
obtain its results, and due to the modelling power of Petri Nets, can consider
complexities such as multi-mission periods, component failure rate
interdependencies, and mission abandonment. The model operates three different
types of Petri Net which interact to provide the overall system reliability modelling
Improving Attack Trees Analysis using Petri Net modeling of Cyber-Attacks
Publisher Copyright:
© 2019 IEEE.Cyber security is one general concern to all network-based organizations. In recent years, by significant increasing cyber-attacks in critical infrastructures (CIs) the need of smart prediction, awareness and protection systems is not deniable. The first step for security assessment is on recognizing and analyzing attacks. In this paper, one of the graphical security assessments named Attack Tree (AT) is used to illustrate one kind of cyber-attacks scenario in Industry 4.0 and the system's behavior is analyzed by Petri Nets.authorsversionpublishe
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