Share This Article:

An Extension to Pi-Calculus for Performance Evaluation

Abstract Full-Text HTML Download Download as PDF (Size:139KB) PP. 9-17
DOI: 10.4236/jsea.2011.41002    4,532 Downloads   8,176 Views   Citations

ABSTRACT

Pi-Calculus is a formal method for describing and analyzing the behavior of large distributed and concurrent systems. Pi-calculus offers a conceptual framework for describing and analyzing the concurrent systems whose configuration may change during the computation. With all the advantages that pi-calculus offers, it does not provide any methods for performance evaluation of the systems described by it; nevertheless performance is a crucial factor that needs to be considered in designing of a multi-process system. Currently, the available tools for pi-calculus are high level language tools that provide facilities for describing and analyzing systems but there is no practical tool on hand for pi-calculus based performance evaluation. In this paper, the performance evaluation is incorporated with pi-calculus by adding performance primitives and associating performance parameters with each action that takes place internally in a system. By using such parameters, the designers can benchmark multi-process systems and compare the performance of different architectures against one another.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

S. Rahimi, E. Khorasani, Y. Lee and B. Gupta, "An Extension to Pi-Calculus for Performance Evaluation," Journal of Software Engineering and Applications, Vol. 4 No. 1, 2011, pp. 9-17. doi: 10.4236/jsea.2011.41002.

References

[1] R. Milner, J. Parrow and D. Walker, “A Calculus of Mobile Processes—Part I and II,” LFCS Report 89-85, University of Edinburgh, Edinburgh, 1989.
[2] R. Milner, “Communicating and Mobile Systems: The π-Calculus,” Cambridge University Press, Cambridge, 1999.
[3] R. Milner, “The Polyadic Pi-Calculus: A Tutorial,” Technical Report ECSLFCS -91-180, Computer Science Department, University of Edinburgh, Edinburgh, 1991.
[4] D. Sangiorgi, “Theπ-Calculus: A Theory of Mobile Processes,” Cambridge University Press, Cambridge, 2001.
[5] D. Sangiorgi: “Expressing Mobility in Process Algebras: First-Order and Higher-Order Paradigms,” Ph.D. Thesis, University of Edinburgh, Edinburgh, 1993.
[6] C. Priami, “Stochasticπ-Calculus,” Computer Journal, Vol. 38, 1995, pp. 578-589. doi:10.1093/comjnl/38.7.578
[7] N. G tz, U. Herzog and M. Rettelbach, “TIPP-A Language for Timed Processes and Performance Evaluation,” Technical Report 4/92. IMMD VII, University of Erlangen-Nurnberg, Erlangen, 1992.
[8] J. Hillston, “A Compositional Approach to Performance Modelling,” Ph.D. Thesis, University of Edinburgh, Edinburgh, 1994.
[9] M. Bernardo, L. Donatiello and R. Gorrieri, “MPA: A Stochastic Process Algebra,” Technial Report UBLCS- 94-10, University of Bologna, Bologna, 1994.
[10] P. Buchholz, “On a Markovian Process Algebra,” Techinal Report Informatik IV, University of Dortmund, Dort- mund 1994.
[11] L. de Alfaro, “Stochastic Transition Systems,” Proceedings of Ninth International Conference on Concurrency Theory (CONCUR’98), Vol. 1477, 1998, pp. 423-438. doi:10.1007/BFb0055639
[12] J. Markovski and E. P. de Vink, “Performance Evaluation of Distributed Systems Based on a Discrete Real- and Stochastic-Time Process Algebra,” Fundamenta Informaticae, Vol. 95, No. 1, October 2009, pp. 157-186.
[13] A. Clark, S. Gilmore, J. Hillston and M. Tribastone, “Stochastic Process Algebras,” SFM’07 Proceedings of the 7th International Conference on Formal Methods for Performance Evaluation, 2007, pp 132-179.
[14] P. R. D’Argenio and J. Katoen, “A Theory of Stochastic Systems. Part II: Process Algebra,” Information and Computation, Vol. 203, No. 1, November 2005, pp. 39-74. doi:10.1016/j.ic.2005.07.002
[15] S. M. Ross, “Stochastic Processes,” 2nd Edition, Wiley, New York, 1996.
[16] G. Bolch, S. Greiner, H. De Meer and K. S. Trivedi, “Queuing Networks and Markov Chains: Modelling and Performance Evaluation with Computer Science Applications,” Wiley, New York, 1998
[17] C. Nottegar, C. Priami and P. Degano, “Performance Evaluation of Mobile Processes Via Abstract Machines,” IEEE Transactions on Software Engineering, Vol. 27, No. 10, 2001, pp. 867-889. doi:10.1109/32.962559
[18] F. Logozzo, “Pi-Calculus as a Rapid Prototype Language For Performance Evaluation,” Proceedings of the ICLP 2001 Workshop on Specification, Analysis and Validation for Emerging Technologies in Computational Logic (SAVE 2001), 2001.
[19] S. Rahimi, M. Cobb, D. Ali, M. Paprzycki and F. Petry, “A Knowledge-Based Multi-Agent System for Geospatial Data Conflation,” Journal of Geographic Information and Decision Analysis, Vol. 6, No. 2, 2002, pp. 67-81.
[20] A. Grama, G. Karypis, V. Kumar and A Gupta, “An Introduction to Parallel Computing: Design and Analysis of Algorithms,” 2nd Edition, Addison Wesley, Reading, 2003
[21] W. R. Cockayne and M. Zyda, “Mobile Agents”, Manning Publications Company, Greenwich, 1998.
[22] H. Samet, “The Design and Analysis of Spatial Data Structures,” Addison-Wesley, Reading, 1989.
[23] S. Rahimi, “Using Api-Calculus for Formal Modeling of SDIAgent: A Multi-Agent Distributed Geospatial Data Integration,” Journal of Geographic Information and Decision Analysis, Vol. 7, No. 2, 2003, pp. 132-149.
[24] S. Rahimi, J. Bjursell, M. Paprzycki, M. Cobb and D. Ali, “Performance Evaluation of SDIAGENT, a Multi-Agent System for Distributed Fuzzy Geospatial Data Conflation,” Information Sciences, Vol. 176, No. 9, 2006. doi:10.1016/ j.ins.2005.07.009
[25] S. Derisavi, P. Kemper and W. H. Sanders, “Symbolic State-Space Exploration and Numerical Analysis of State-Sharing Composed Models,” Linear Algebra and Its Applications, Vol. 386, July 2004, pp. 137-166. doi:10. 1016/j.laa.2004.01.006
[26] S. Derisavi, H. Hermanns and W. H. Sanders, “Optimal State-Space Lumping in Markov Chains,” Information Processing Letters, Vol. 87, No. 6, 2003, pp. 309-315. doi:10.1016/S0020-0190(03)00343-0
[27] P. Buchholz, “Efficient Computation of Equivalent and Reduced Representations for Stochastic Automata,” International Journal of Computer Systems Science & Engineering, Vol. 15, No. 2, March 2000, pp. 93-103.

  
comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.