The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.01 - Jan. (2013 vol.39)
pp: 97-118
Richard A. Hayden , Imperial College London, London
Jeremy T. Bradley , Imperial College London, London
Allan Clark , University of Edinburgh, Edinburgh
ABSTRACT
Rapid and accessible performance evaluation of complex software systems requires two critical features: the ability to specify useful performance metrics easily and the capability to analyze massively distributed architectures, without recourse to large compute clusters. We present the unified stochastic probe, a performance specification mechanism for process algebra models that combines many existing ideas: state and action-based activation, location-based specification, many-probe specification, and immediate signaling. These features, between them, allow the precise and compositional construction of complex performance measurements. The paper shows how a subset of the stochastic probe language can be used to specify common response-time measures in massive process algebra models. The second contribution of the paper is to show how these response-time measures can be analyzed using so-called fluid techniques to produce rapid results. In doing this, we extend the fluid approach to incorporate immediate activities and a new type of response-time measure. Finally, we calculate various response-time measurements on a complex distributed wireless network of O(10^{129}) states in size.
INDEX TERMS
Probes, Stochastic processes, Analytical models, Algebra, Computational modeling, Semantics, Syntactics, passage-time analysis, Performance modeling, performance evaluation tools, stochastic process algebra, measurement probes, fluid approximation
CITATION
Richard A. Hayden, Jeremy T. Bradley, Allan Clark, "Performance Specification and Evaluation with Unified Stochastic Probes and Fluid Analysis", IEEE Transactions on Software Engineering, vol.39, no. 1, pp. 97-118, Jan. 2013, doi:10.1109/TSE.2012.1
REFERENCES
[1] A.L. Wolf and D.S. Rosenblum, "A Study in Software Process Data Capture and Analysis," Proc. Second Int'l Conf. Software Process, pp. 115-124, Feb./Mar. 1993.
[2] A. Argent-Katwala, J.T. Bradley, and N.J. Dingle, "Expressing Performance Requirements Using Regular Expressions to Specify Stochastic Probes over Process Algebra Models," Proc. Fourth Int'l Workshop Software and Performance, pp. 49-58, 2004.
[3] A. Argent-Katwala, J. Bradley, A. Clark, and S. Gilmore, "Location-Aware Quality of Service Measurements for Service-Level Agreements," Proc. Third Int'l Conf. Trustworthy Global Computing, pp. 222-239, 2008.
[4] A. Clark and S.T. Gilmore, "Transformations in PEPA Models and Stochastic Probe Placement," Proc. 25th UK Performance Eng. Workshop, K. Djemame, ed., pp. 1-16, 2009.
[5] A. Clark and S.T. Gilmore, "State-Aware Performance Analysis with eXtended Stochastic Probes," Proc. Fifth European Performance Eng. Workshop, N. Thomas and C. Juiz, eds., pp. 125-140, 2008.
[6] R.A. Hayden, A. Stefanek, and J.T. Bradley, "Fluid Computation of Passage Time Distributions in Large Markov Models," Theoretical Computer Science, vol. 413, pp. 106-141, Jan. 2012.
[7] A. Aziz, K. Sanwal, V. Singhal, and R. Brayton, "Verifying Continuous-Time Markov Chains," Proc. Eighth Int'l Conf. Computer-Aided Verification, pp. 269-276, 1996.
[8] H. Hermanns, J.-P. Katoen, J. Meyer-Kayser, and M. Siegle, "Towards Model Checking Stochastic Process Algebra," Proc. Second Int'l Conf. Integrated Formal Methods, pp. 420-439, Nov. 2000.
[9] C. Baier, L. Cloth, B.R. Haverkort, M. Kuntz, and M. Siegle, "Model Checking Markov Chains with Actions and State Labels," IEEE Trans. Software Eng., vol. 33, no. 4, pp. 209-224, Apr. 2007.
[10] S. Donatelli, S. Haddad, and J. Sproston, "Model Checking Timed and Stochastic Properties with ${\rm CSL}^{\rm TA}$ ," IEEE Trans. Software Eng., vol. 35, no. 2, pp. 224-240, Mar. 2009.
[11] C.M. Woodside and C. Shramm, "Complex Performance Measurements with NICE (Notation for Interval Combinations and Events)," Software—Practice and Experience, vol. 24, pp. 1121-1144, Dec. 1994.
[12] W.J. Knottenbelt and P.G. Harrison, "Distributed Disk-Based Solution Techniques for Large Markov Models," Proc. Third Int'l Conf. the Numerical Solution of Markov Chains, pp. 58-75, Sept. 1999.
[13] M. Kwiatkowska, G. Norman, and D. Parker, "PRISM: Probabilistic Symbolic Model Checker," Proc. 12th Int'l Conf. Modelling Techniques and Tools for Computer Performance Evaluation, pp. 200-204, 2002.
[14] D.D. Deavours, G. Clark, T. Courtney, D. Daly, S. Derisavi, J.M. Doyle, W.H. Sanders, and P.G. Webster, "The Möbius Framework and Its Implementation," IEEE Trans. Software Eng., vol. 28, no. 10, pp. 956-969, Oct. 2002.
[15] M. Kuntz and M. Siegle, "Symbolic Model Checking of Stochastic Systems: Theory and Implementation," Proc. 13th Int'l SPIN Workshop Model Checking Software, pp. 89-107, 2006.
[16] S. Gilmore, J. Hillston, and M. Ribaudo, "An Efficient Algorithm for Aggregating PEPA Models," IEEE Trans. Software Eng., vol. 27, no. 5, pp. 449-464, May 2001.
[17] M.A. Marsan, G. Conte, and G. Balbo, "A Class of Generalized Stochastic Petri Nets for the Performance Evaluation of Multiprocessor Systems," ACM Trans. Computer Systems, vol. 2, pp. 93-122, May 1984.
[18] H. Hermanns, Interacting Markov Chains and the Quest for Quantified Quality. Springer, 2002.
[19] R.A. Hayden and J.T. Bradley, "A Fluid Analysis Framework for a Markovian Process Algebra," Theoretical Computer Science, vol. 411, pp. 2260-2297, May 2010.
[20] J. Hillston, A Compositional Approach to Performance Modelling. Cambridge Univ. Press, 1996.
[21] R.A. Hayden and J.T. Bradley, "A Fluid Analysis Framework for a Markovian Process Algebra," Theoretical Computer Science, vol. 411, pp. 2260-2297, May 2010, doi: //10.1016/j.tcs.2010.02.001.
[22] R.A. Hayden, "Scalable Performance Analysis of Massively Parallel Stochastic Systems," PhD thesis, Imperial College London, http://pubs.doc.ic.ac.ukhayden-thesis/, 2011.
[23] M. Sipser, Introduction to the Theory of Computation. PWS, 1997.
[24] R. Serfozo, Basics of Applied Stochastic Processes. Springer, 2009.
[25] E.G. Amparore, M. Beccuti, S. Donatelli, and G. Franceschinis, "Probe Automata for Passage Time Specification," Proc. Eighth Int'l Conf. Quantitative Evaluation of Systems, pp. 101-110, 2011.
[26] H.R. Neave, Statistics Tables for Mathematicians, Engineers, Economists and the Behavioural and Management Sciences. George Allen & Unwin, 1978.
[27] A. Stefanek, R.A. Hayden, and J.T. Bradley, "A New Tool for the Performance Analysis of Massively Parallel Computer Systems," Proc. Eighth Workshop Quantitative Aspects of Programming Languages, pp. 159-181, 2010.
[28] A. Stefanek, R.A. Hayden, and J.T. Bradley, "GPA—A Tool for Fluid Scalability Analysis of Massively Parallel Systems," Proc. Eighth Int'l Conf. Quantitative Evaluation of Systems, pp. 147-148, http://pubs.doc.ic.ac.ukgpanalyser/, 2011.
[29] A. Tari, M. Telek, and P. Buchholz, "A Unified Approach to the Moments Based Distribution Estimation—Unbounded Support," Proc. Int'l Conf. European Performance Eng., and Web Services and Formal Methods, Int'l Conf. Formal Techniques for Computer Systems and Business Processes, pp. 79-93, 2005.
64 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool