Time scale decomposition of a class of generalized stochastic Petri net models

Ammar, H.H.; Islam, S.M.R.

doi:10.1109/32.24734

Cited by 66 publications

(17 citation statements)

References 11 publications

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“…A weakness of PN is state space explosion problem which is not involved in this paper. The method to solve this problem can be found in [16], [17] and [14].…”

Section: B Related Workmentioning

confidence: 99%

Modeling of Scheduling Algorithms of Downstream Channel Bonding in DOCSIS3.0 Based on GSPN

Zhao

Zhou

2013

2013 European Modelling Symposium

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For QoS of service flows, it is essential to study on multi-channel load balancing and scheduling problems in Data Over Cable Service Interface Specifications (DOCSIS3.0). In this article, we studied downstream multi-channel load balancing and scheduling in DOCSIS3.0 by mean of Generalized Stochastic Petri Net (GSPN). We presented the model for two queuing mechanisms including the output queuing architecture and the input queuing architecture using GSPN, and described load balancing algorithms including Random Selecting (RS) and Shortest Expected Delay (SED), packets scheduling algorithms including Queue Length Threshold (QLT), Deficit Round Robin (DRR) and Bonded DRR (BDRR) based on GSPN model. In order to improve the delay performance of real-time service flow, we proposed Queue Threshold DRR (QTDRR) algorithm. Then we analyzed and evaluated SED-DRR.SED-QTDRR, RS-BDRR, RS-QTDRR on the basis of the theory and tool of GSPN. Our results show that QTDRR algorithm can improve the delay characteristic of real-time flows without affecting throughput.

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“…A weakness of PN is state space explosion problem which is not involved in this paper. The method to solve this problem can be found in [16], [17] and [14].…”

Section: B Related Workmentioning

confidence: 99%

Modeling of Scheduling Algorithms of Downstream Channel Bonding in DOCSIS3.0 Based on GSPN

Zhao

Zhou

2013

2013 European Modelling Symposium

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“…Stochastic Petri net (SPN) classes, often used for perfor mance analysis, rely on a set of decompositions approaches (such as [14] [IS] [16]), to reduce the analysis complexity. In [IS] a decomposition approach is presented to support the analysis of large stochastic Petri nets, reducing the size of the generated state space graphs.…”

Section: A Supporting Behavioral Analysismentioning

confidence: 99%

Extending a net splitting operation for decomposition of high-level Petri nets

Moutinho

Gomes

2012

IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society

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This paper presents an extension to a net split ting operation for decomposition of high -level Petri nets, to support distributed implementations of embedded systems. The net splitting operation, selected from the survey of methods summarized in this paper, was originally proposed for low-level Petri nets. The advantages of the selected method are its higher flexibility on the cutting set definition, and the generation of sub-models in interaction with adequate support to implement its communication channels. High -level Petri net classes are extended to support the application of the new net operation, and additional tasks to be performed are identified. Finally, an example is used to illustrate the application of the net operation to a high-level Petri net model.

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“…The failures of primary modules and related rollback processes are slow activities. A formal representation of TSD for stochastic Petri nets is given in [1]. First, we only consider the activities at the fast time scale.…”

Section: An Example Of Performability Analysis Of a Fault-tolerant DImentioning

confidence: 99%

Time warp simulation using time scale decomposition

Ammar¹

1992

ACM Trans. Model. Comput. Simul.

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In this paper we consider time scale decomposition as well as spatial decomposition to induce massive parallelism and reduce overhead in distributed discrete-event simulations. We confine our study to the Time Warp strategy and to systems where the durations of activities differ by several orders of magnitude (i.e., systems with fast and slow activities). We show that, for such systems, a large overhead due to rollbacks is encountered when spatial decomposition is used. Moreover, performance degrades as the difference increases between the rates of fast and slow events. Several initial experiments using queueing-network models were designed to evaluate the effectiveness of time scale decomposition in increasing the parallelism and reducing the overhead. These experiments were conducted on a distributed simulation testbed that was implemented on an 18-processor Multimax 320. The application of the above simulation techniques to stochastic Petri net models is illustrated using an example of performability analysis of a fault-tolerant distributed system.

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Time scale decomposition of a class of generalized stochastic Petri net models

Cited by 66 publications

References 11 publications

Modeling of Scheduling Algorithms of Downstream Channel Bonding in DOCSIS3.0 Based on GSPN

Modeling of Scheduling Algorithms of Downstream Channel Bonding in DOCSIS3.0 Based on GSPN

Extending a net splitting operation for decomposition of high-level Petri nets

Time warp simulation using time scale decomposition

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