Former group member (MS, 1992; Ph.D., 1996).
Publications with the Performability Engineering Research Group
Performability Modeling with UltraSAN.
J. Couvillion, R. Freire, R. Johnson, W. D. Obal II, M. A. Qureshi, M. Rai, W. H. Sanders, and J. E. Tvedt. (91C01)
IEEE Software, vol. 8, no. 5, Sept. 1991, pp. 69-80. [IEEE Xplore entry]
Overview paper on UltraSAN. Provides a basic introduction to the package.
Performability Modeling with UltraSAN.
J. Couvillion, R. Freire, R. Johnson, W. D. Obal II, M. A. Qureshi, M. Rai, W. H. Sanders, and J. E. Tvedt. (91C02, available in hard copy)
Proceedings of the 4th International Workshop on Petri Nets and Performance Models, Melbourne, Australia, December 2-5, 1991, pp. 290-299. [IEEE Xplore entry]
Conference version of above paper.
Reward Model Solution Methods with Impulse and Rate Rewards: An Algorithm and Numerical Results.
M. A. Qureshi. (92Q01)
Master’s Thesis, University of Arizona, 1992.
Reward Model Solution Methods with Impulse and Rate Rewards: An Algorithm and Numerical Results.
W. H. Sanders and M. A. Qureshi.
2nd ORSA Telecommunications Conference, Boca Raton, FL, Mar. 1992.
Reward Model Solution Methods with Impulse and Rate Rewards: An Algorithm and Numerical Results.
M. A. Qureshi and W. H. Sanders. (94QUR01)
Performance Evaluation, vol. 20, 1994, pp. 413-436.
Presents a method to compute performability distribution of reward models with impulse and rate rewards. [published version and erratum from Elsevier]
The Effect of Workload on the Performance and Availability of Voting Algorithms.
M. A. Qureshi and W. H. Sanders. (95QUR01)
Proceedings of the International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS ’95), Durham, NC, January 18-20, 1995, pp. 217-224. [IEEE Xplore entry]
Modeling study of voting algorithms.
UltraSAN Version 3: Architecture, Features, and Implementation.
W. H. Sanders, W. D. Obal II, M. A. Qureshi, and F. K. Widjanarko. (95S02)
Proceedings of the AIAA Computing in Aerospace 10 Conference, San Antonio, TX, March 28-30, 1995, pp. 327-338.
Discussion of the features and architecture of UltraSAN Version 3.0, with an example.
UltraSAN Version 3 Overview.
D. D. Deavours, W. D. Obal II, M. A. Qureshi, W. H. Sanders, and A. P. A. van Moorsel. (95DEA01)
Proceedings of the Sixth International Workshop on Petri Nets and Performance Models, Durham, NC, October 3-6, 1995, pp. 216-217. [IEEE Xplore entry]
A two-page overview of UltraSAN Version 3.0.
Algorithms for the Generation of State-Level Representations of Stochastic Activity Networks with General Reward Structures.
M. A. Qureshi, W. H. Sanders, A. P. A. van Moorsel, and R. German. (95Q02)
Proceedings of the Sixth International Workshop on Petri Nets and Performance Models, Durham, NC, October 3-6, 1995, pp. 180-190. [IEEE Xplore entry]
This paper discusses the generation of the stochastic process underlying a SAN, including the algorithm for the well-specified check. Furthermore, a general reward structure is introduced that can represent all reward variables defined on the marking behavior of a SAN.
The UltraSAN Modeling Environment.
W. H. Sanders, W. D. Obal II, M. A. Qureshi, and F. K. Widjanarko. (95S01)
Performance Evaluation, vol. 24, no. 1, October-November 1995, pp. 89-115.
Overview of UltraSAN Version 3.0.
The Effect of Workload on the Performance and Availability of Voting Algorithms.
M. A. Qureshi and W. H. Sanders. (95QUR03)
Microelectronics and Reliability, Special Issue on Performance Modeling and Reliability Analysis, June 1996, vol. 36, no. 6, pp. 757-774.
Expected Impulse Rewards in Markov Regenerative Stochastic Petri Nets.
R. German, A. P. A. van Moorsel, M. A. Qureshi, and W. H. Sanders. (95GER01)
Application and Theory of Petri Nets, Proceedings of the 17th International Conference, Osaka, Japan, June 24-28, 1996, pp. 172-191 (ed. J. Billington and W. Reisig), Lecture Notes in Computer Science, Vol. 1091, Springer-Verlag, 1996.
Computes reward measures for Petri nets with general distributions. Furthermore, the method of supplementary variables is enhanced to derive transient solutions of models with general distributions.
A New Methodology for Calculating Distributions of Reward Accumulated During a Finite Interval.
M. A. Qureshi and W. H. Sanders. (95QUR04)
Proceedings of the 26th International Symposium on Fault-Tolerant Computing, Sendai, Japan, June 1996, pp. 116-125. [IEEE Xplore entry]
This paper presents a new method to compute the distribution of reward accumulated during a finite interval in a Markov reward model. It does this by computing probabilities of particular paths in a uniformized version of the process, and computing the conditional distribution of reward accumulated, given a path.
Algorithms for the Generation of State-Level Representations of Stochastic Activity Networks with General Reward Structures.
M. A. Qureshi, W. H. Sanders, A. P. A. van Moorsel, and R. German. (95QUR05)
IEEE Transactions on Software Engineering, vol. 22, no. 9, September 1996, pp. 603-614. [IEEE Xplore entry]
Same description as for conference version, above.
Overview of UltraSAN.
W. D. Obal II, M. A. Qureshi, D. D. Deavours, and W. H. Sanders. (96OBA01)
Proc. IEEE Int. Performance and Dependability Symposium, Urbana, IL, Sept. 4-6, 1996. [IEEE Xplore entry]
Construction and Solution of Markov Reward Models.
M. A. Qureshi. (96QUR02)
Doctoral Dissertation, University of Arizona, 1996.
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