skip to main content
article

The ORIS tool: app, library, and toolkit for quantitative evaluation of non-Markovian systems

Published: 06 June 2022 Publication History

Abstract

ORIS is a tool for quantitative modeling and evaluation of concurrent systems with non-Markovian durations. It provides a Graphical User Interface (GUI) for model specification as Stochastic Time Petri Nets (STPNs), validation by interactive simulation, and evaluation by several techniques, computing instantaneous and cumulative rewards. It also provides an open-source Java Application Programming Interface (API) to automate the workflow, and it can be used as a toolkit for derivation and evaluation of STPNs in model driven engineering. As distinguishing features, ORIS implements transient and steady-state analysis of STPNs with underlying Markov Regenerative Process (MRP), and transient analysis of STPNs with underlying Generalized Semi- Markov Process (GSMP). It also implements nondeterministic analysis of Time Petri Nets (TPNs), simulation of STPNs, and solution methods for Continuous-Time Markov Chains (CTMCs) and MRPs with at most one non-exponential timer in each state. The well-engineered software architecture of ORIS supports agile implementation of new STPN features, new modeling formalisms, and new analysis methods.

References

[1]
M. Ajmone Marsan, G. Conte, and G. Balbo. A class of generalized stochastic Petri nets for the performance evaluation of multiprocessor systems. ACM Trans. Comput. Syst., 2(2):93--122, May 1984.
[2]
E. G. Amparore, G. Balbo, M. Beccuti, S. Donatelli, and G. Franceschinis. 30 Years of GreatSPN, chapter In: Principles of Performance and Reliability Modeling and Evaluation: Essays in Honor of Kishor Trivedi, pages 227--254. Springer, Cham, 2016.
[3]
G. Behrmann, A. David, and K. G. Larsen. A tutorial on uppaal. In SFM-RT'04, number 3185 in LNCS, pages 200--236. Springer--Verlag, September 2004.
[4]
B. Berthomieu and M. Diaz. Modeling and Verification of Time Dependent Systems Using Time Petri Nets. IEEE TSE, 17(3):259--273, 1991.
[5]
B. Berthomieu, P.-O. Ribet, and F. Vernadat. The tool TINA -- construction of abstract state spaces for Petri Nets and Time Petri Nets. International Journal of Production Research, 42(14), 2004.
[6]
M. Biagi, L. Carnevali, M. Paolieri, F. Patara, and E. Vicario. A continuous-time model-based approach for activity recognition in pervasive environments. IEEE Trans. on Human-Machine Systems, 49(4):293--303, 2019.
[7]
M. Biagi, L. Carnevali, M. Paolieri, and E. Vicario. Performability evaluation of the ERTMS/ETCS - Level 3. Transportation Research Part C: Emerging Technologies, 82:314--336, 2017.
[8]
M. Biagi, L. Carnevali, F. Tarani, and E. Vicario. Model-based quantitative evaluation of repair procedures in gas distribution networks. ACM Trans. on Cyber-Physical Systems, 3(2):19:1--19:26, Dec. 2018.
[9]
L. Carnevali, C. Nugent, F. Patara, and E. Vicario. A Continuous-Time Model-Based Approach to Activity Recognition for Ambient Assisted Living. In QEST'15, pages 38--53. Springer, 2015.
[10]
L. Carnevali, L. Ridi, and E. Vicario. A quantitative approach to input generation in real-time testing of stochastic systems. IEEE TSE, 39(3):292--304, 2013.
[11]
L. Carnevali, F. Tarani, and E. Vicario. Performability evaluation of water distribution systems during maintenance procedures. IEEE Trans. on Systems, Man and Cybernetics: Systems, to appear.
[12]
G. Gardey, D. Lime, M. Magnin, and O. Roux. Rom´eo: a tool for analyzing Time Petri Nets. CAV'05, 2005.
[13]
S. Garg, A. Puliafito, M. Telek, and K. Trivedi. Analysis of preventive maintenance in transactions based software systems. IEEE TC, 47(1):96--107, 1998.
[14]
S. Garg, A. Puliafito, M. Telek, and K. S. Trivedi. Analysis of software rejuvenation using Markov Regenerative Stochastic Petri Net. In ISSRE'95, pages 180--187, 1995.
[15]
R. German. Iterative analysis of Markov regenerative models. Perform. Eval., 44(1--4):51--72, 2001.
[16]
R. German, D. Logothetis, and K. S. Trivedi. Transient analysis of Markov regenerative stochastic Petri nets: a comparison of approaches. In PNPM'95, pages 103--112, 1995.
[17]
L. Grunske. Specification patterns for probabilistic quality properties. In ICSE'08, pages 31--40. ACM, May 2008.
[18]
A. Horv´ath, M. Paolieri, L. Ridi, and E. Vicario. Transient analysis of non-Markovian models using stochastic state classes. Perform. Eval., 69(7--8):315--335, July 2012.
[19]
A. Horv´ath and M. Telek. PhFit: A General Phase-Type Fitting Tool. In Computer Performance Evaluation, Modelling Techniques and Tools (TOOLS'02), pages 82--91, 2002.
[20]
Y. Huang, C. M. R. Kintala, N. Kolettis, and N. D. Fulton. Software Rejuvenation: Analysis, Module and Applications. In International Symposium on Fault-Tolerant Computing, pages 381--390, 1995.
[21]
V. Kulkarni. Modeling and analysis of stochastic systems. Chapman & Hall, 1995.
[22]
M. Kwiatkowska, G. Norman, and D. Parker. PRISM 4.0: verification of probabilistic real-time systems. In CAV'11, volume 6806 of LNCS, pages 585--591. Springer, 2011.
[23]
ORIS. Homepage. http://www.oris-tool.org, 2021.
[24]
M. Paolieri, M. Biagi, L. Carnevali, and E. Vicario. The ORIS Tool: Quantitative Evaluation of Non-Markovian Systems. IEEE Trans. on Soft. Eng., 47:1211--1225, 2021.
[25]
M. Paolieri, A. Horv´ath, and E. Vicario. Probabilistic Model Checking of Regenerative Concurrent Systems. IEEE TSE, 42(2):153--169, Feb 2016.
[26]
P. Reinecke, T. Krauß, and K. Wolter. Phase-Type Fitting Using HyperStar. In EPEW'13, pages 164--175, 2013.
[27]
F. Salfner and K. Wolter. Analysis of service availability for time-triggered rejuvenation policies. Journal of Sys. and Soft., 83(9):1579 -- 1590, 2010.
[28]
W. H. Sanders and J. F. Meyer. Stochastic activity networks: formal definitions and concepts. In School Europ. Educ. Forum, pages 315--343. Springer, 2000.
[29]
SIRIO. https://github.com/oris-tool/sirio, 2021.
[30]
W. J. Stewart. Introduction to the Numerical Solution of Markov Chains. Princeton University Press, 1995.
[31]
K. S. Trivedi. Probability and statistics with reliability, queuing, and computer science applications. John Wiley and Sons, New York, 2001.
[32]
K. S. Trivedi and R. Sahner. SHARPE at the Age of Twenty Two. SIGMETRICS Perform. Eval. Rev., 36(4):52--57, Mar. 2009.
[33]
A. van Moorsel and K. Wolter. Analysis of restart mechanisms in software systems. IEEE TSE, 32(8):547--558, Aug 2006.
[34]
E. Vicario. Static analysis and dynamic steering of time-dependent systems. IEEE TSE, 27(8):728--748, Aug. 2001.
[35]
E. Vicario, L. Sassoli, and L. Carnevali. Using stochastic state classes in quantitative evaluation of dense-time reactive systems. IEEE TSE, 35(5):703--719, Sept./Oct. 2009.
[36]
W. Whitt. Approximating a point process by a renewal process, I: Two basic methods. Operations Research, 30(1):125--147, 1982.
[37]
A. Zimmermann. Modelling and Performance Evaluation with TimeNET 4.4. In QEST'17, pages 300--303, 2017.

Cited By

View all

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM SIGMETRICS Performance Evaluation Review
ACM SIGMETRICS Performance Evaluation Review  Volume 49, Issue 4
March 2022
130 pages
ISSN:0163-5999
DOI:10.1145/3543146
Issue’s Table of Contents
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 June 2022
Published in SIGMETRICS Volume 49, Issue 4

Check for updates

Author Tags

  1. markov regenerative processes
  2. model driven engineering.
  3. non-markovian processes
  4. quantitative evaluation
  5. software tools and libraries
  6. stochastic models
  7. stochastic petri nets

Qualifiers

  • Article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 41
    Total Downloads
  • Downloads (Last 12 months)14
  • Downloads (Last 6 weeks)1
Reflects downloads up to 20 Jan 2025

Other Metrics

Citations

Cited By

View all

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media