NDLI: Computing first passage time distributions in stochastic well-formed nets

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Computing first passage time distributions in stochastic well-formed nets

Content Provider	ACM Digital Library
Author	De Pierro, Massimiliano Beccuti, Marco Balbo, Gianfranco Franceschini, Giuliana
Abstract	The increasing demand for customer centric evaluation of systems, mostly related with the assessment of the quality of service that they can deliver, requires the development of techniques properly designed to model and to study the movement of specific entities generically referred to as "customers". Stochastic Well-Formed Net(SWN) are naturally suited for the representation of systems in which "customers" of different categories compete for the use of common resources. Color classes of SWN are easily associated with these different categories, leaving to the peculiar features of the formalism the possibility of exploiting all the symmetries existing into the representation for the efficient and effective computation of the measures of interest. Within this application context, the computation of first passage time distribution measures in Stochastic Well-Formed Net (SWN) is becoming of primary interest. Customers however are not primitive entities in the formalism and an approach similar to that previously developed for Generalized Stochastic Petri Nets (GSPN) is suggested to overcome this problem in which P-semiflows are used to identify the circulating "customers". In this paper we propose an original algorithm for computing some P-semiflows of colored PNs (in particular of SWNs) in parametric form by exploiting the peculiarities of the objective of this investigation, and extend the customer centric first passage time computation approach previously developed for GSPNs, to make it suitable for SWN models. Moreover, the paper proposes an enhancement of the SWN notation in order to provide a way to ease the modeler in the specification of customer scheduling policies that may affect the computation of first passage time distributions. This extension, inspired by Queueing Petri Nets, adds to SWN some "syntactic sugar" that allows to include in the model queueing places which are automatically replaced by appropriate submodels, before solving the model.
Starting Page	7
Ending Page	18
Page Count	12
File Format	PDF
ISBN	9781450305198
DOI	10.1145/1958746.1958754
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-03-14
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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