Performance Analysis Using Stochastic Petri Nets

Molloy, Barry

doi:10.1109/tc.1982.1676110

Cited by 881 publications

(328 citation statements)

References 13 publications

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“…Therefore we adopt ordinary stochastic Petri nets (SPNs) to model and evaluate the performance. Stochastic Petri nets is a powerful tool for system performance evaluation [21][22][23]. In this paper, the basic theory of stochastic Petri nets is applied to model and evaluate performance of storage systems.…”

Section: Performance Evaluationmentioning

confidence: 99%

A Retrieval Optimized Surveillance Video Storage System for Campus Application Scenarios

Chen

et al. 2018

Journal of Electrical and Computer Engineering

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This paper investigates and analyzes the characteristics of video data and puts forward a campus surveillance video storage system with the university campus as the specific application environment. Aiming at the challenge that the content-based video retrieval response time is too long, the key-frame index subsystem is designed. The key frame of the video can reflect the main content of the video. Extracted from the video, key frames are associated with the metadata information to establish the storage index. The key-frame index is used in lookup operations while querying. This method can greatly reduce the amount of video data reading and effectively improves the query's efficiency. From the above, we model the storage system by a stochastic Petri net (SPN) and verify the promotion of query performance by quantitative analysis.

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Section: Performance Evaluationmentioning

confidence: 99%

A Retrieval Optimized Surveillance Video Storage System for Campus Application Scenarios

Chen

et al. 2018

Journal of Electrical and Computer Engineering

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“…In Stochastic Petri Nets (SPN) [32] all the transitions are assumed to fire with a random delay that is exponentially distributed. This feature enriches the analysis of a variety of systems by computing several quantitative indices on their efficiency (performance) and reliability.…”

Section: From Petri Nets To Gspnmentioning

confidence: 99%

30 Years of GreatSPN

Amparore

Balbo

Beccuti

et al. 2016

Springer Series in Reliability Engineering

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GreatSPN is a tool for the stochastic analysis of systems modelled as (stochastic) Petri nets. This chapter describes the evolution of the GreatSPN framework over its lifespan of 30 years, from the first stochastic Petri net analyzer implemented in Pascal, to the current, fancy, graphical interface that supports a number of different model analyzers. This chapter reviews, with the help of a manufacturing system example, how GreatSPN is currently used for an integrated qualitative and quantitative analysis of Petri net systems, ranging from symbolic model checking techniques to a stochastic analysis whose efficiency is boosted by lumpability.

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“…[Kienhuis et al, 1997] finds a satisfactory architecture design, mapping and structure for the algorithms. Important requirements for the models and modelling techniques are: [Jensen, 1992], timed Petri nets [Zuberek, 1991], stochastic delays [Molloy, 1982] and hierarchy provide expressive modelling power. These Petri net concepts are supported by the tool ExSpect [ASPT, 1994].…”

Section: Problem Statementmentioning

confidence: 99%

Performance Analysis of Dataflow Architectures Using Timed Coloured Petri Nets

Witlox

Wolf

Aarts

et al. 2000

Hardware Design and Petri Nets

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Abstract. We present an approach to model dataflow architectures at a high level of abstraction using timed coloured Petri nets. We specifically examine the value of Petri nets for evaluating the performance of such architectures. For this purpose we assess the value of Petri nets both as a modelling technique for dataftow architectures and as an analysis tool that yields valuable performance data for such architectures through the execution of Petri net models. Because our aim is to use the models for performance analysis, we focus on representing the timing and communication behaviour of the architecture rather than the functionality. A modular approach is used to model architectures. We identify five basic hardware building blocks from which Petri net models of dataflow architectures can be constructed. In defining the building blocks we will identify strengths and weaknesses of Petri nets for modelling dataflow architectures. A technique called folding is applied to build generic models of dataflow architectures. A timed coloured Petri net model of the Prophid data.flow architecture, which is being developed at Philips Research Laboratories, is presented. This model has been designed in the tool ExSpect. The performance of the Prophid architecture has been analysed by simulation with this model.

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Performance Analysis Using Stochastic Petri Nets

Cited by 881 publications

References 13 publications

A Retrieval Optimized Surveillance Video Storage System for Campus Application Scenarios

A Retrieval Optimized Surveillance Video Storage System for Campus Application Scenarios

30 Years of GreatSPN

Performance Analysis of Dataflow Architectures Using Timed Coloured Petri Nets

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