Software development for analysis of stochastic petri nets using transfer functions

This thesis research is an implementation of a closed-form analytical technique for study, evaluation and analysis of Stochastic Petri Nets (SPN). The technique is based on a theorem that an isomorphism exists between an SPN and a Markov Chain. The procedure comprises five main steps: reachability graph generation of the underlying Petri net, transformation of the reachability graph to a state machine Petri net, calculation of transfer functions, computation of equivalent transfer functions via Mason\u27s rule, and computation of performance parameters of the SPN model from the equivalent transfer functions and their derivatives. The software is developed in UNIX using C and applied to various SPN models. Future research includes implementation of Mason\u27s rule for complex cases and symbolic derivation of equivalent transfer functions

Computer implementation of Mason\u27s rule and software development of stochastic petri nets

A symbolic performance analysis approach for discrete event systems can be formulated based on the integration of Petri nets and Moment Generating Function concepts [1-3]. The key steps in the method include modeling a system with arbitrary stochastic Petri nets (ASPN), generation of state machine Petri nets with transfer functions, derivation of equivalent transfer functions, and symbolic derivation of transfer functions to obtain the performance measures. Since Mason\u27s rule can be used to effectively derive the closed-form transfer function, its computer implementation plays a very important role in automating the above procedure. This thesis develops the computer implementation of Mason\u27s rule (CIMR). The algorithms and their complexity analysis are also given. Examples are used to illustrate CIMR method\u27s application for performance evaluation of ASPN and linear control systems. Finally, suggestions for future software development of ASPN are made

Stepwise reduction and approximation method for performance analysis of generalized stochastic petri nets

This thesis delves into the performance analysis of generalized stochastic Petri net (GSPN) model by using an approximation method: the Stepwise Reduction and Approximation (SRA) Method. The key point is that we are able to analyze a subnet in isolation by keeping its token flow direction and its sub-throughput equivalent with all the possible tokens entering into the subnet. The thesis first defines various kinds of potentially reducible subnets, subnet selection rules, approximation subnet construction rules, and reduction evaluation rules. Then corresponding to the possible subnets, the approximation method is used stepwisely until the interested measures are found with the global state space reduced. Two GSPN model examples from the literature are analyzed by using the proposed method. The approximation errors are given and discussed. Finally, the conclusions are drawn and future research is discussed

Constructing Matrix Exponential Distributions by Moments and Behavior around Zero

This paper deals with moment matching of matrix exponential (ME) distributions used to approximate general probability density functions (pdf). A simple and elegant approach to this problem is applying Padé approximation to the moment generating function of the ME distribution. This approach may, however, fail if the resulting ME function is not a proper probability density function; that is, it assumes negative values. As there is no known, numerically stable method to check the nonnegativity of general ME functions, the applicability of Padé approximation is limited to low-order ME distributions or special cases. In this paper, we show that the Padé approximation can be extended to capture the behavior of the original pdf around zero and this can help to avoid representations with negative values and to have a better approximation of the shape of the original pdf. We show that there exist cases when this extension leads to ME function whose nonnegativity can be verified, while the classical approach results in improper pdf. We apply the ME distributions resulting from the proposed approach in stochastic models and show that they can yield more accurate results

Performance Evaluation of CORBA Concurrency Control Service Using Stochastic Petri Nets

The interest in performance evaluation of middleware systems is increasing. Measurement techniques are still predominant among those used to carry out performance evaluation. However, performance models are currently being defined due to their flexibility, precision and facilities to carry out capacity planning activities. This paper presents stochastic Petri net models for performance evaluation of the CORBA Concurrency Control Service (CCS), which mediates concurrent access to objects. In order to validate the proposed models, CCS performance results obtained using those models are then compared against ones obtained through actual measurements.The interest in performance evaluation of middleware systems is increasing. Measurement techniques are still predominant among those used to carry out performance evaluation. However, performance models are currently being defined due to their flexibility, precision and facilities to carry out capacity planning activities. This paper presents stochastic Petri net models for performance evaluation of the CORBA Concurrency Control Service (CCS), which mediates concurrent access to objects. In order to validate the proposed models, CCS performance results obtained using those models are then compared against ones obtained through actual measurements

A Markov Chain Model Checker

Markov chains are widely used in the context of performance and reliability evaluation of systems of various nature. Model checking of such chains with respect to a given (branching) temporal logic formula has been proposed for both the discrete [17,6] and the continuous time setting [4,8]. In this paper, we describe a prototype model checker for discrete and continuous-time Markov chains, the Erlangen Twente Markov Chain Checker $(E \vdash MC^2$), where properties are expressed in appropriate extensions of CTL. We illustrate the general bene ts of this approach and discuss the structure of the tool. Furthermore we report on first successful applications of the tool to non-trivial examples, highlighting lessons learned during development and application of $(E \vdash MC^2$)

Performance evaluation of an emergency call center: tropical polynomial systems applied to timed Petri nets

We analyze a timed Petri net model of an emergency call center which processes calls with different levels of priority. The counter variables of the Petri net represent the cumulated number of events as a function of time. We show that these variables are determined by a piecewise linear dynamical system. We also prove that computing the stationary regimes of the associated fluid dynamics reduces to solving a polynomial system over a tropical (min-plus) semifield of germs. This leads to explicit formul{\ae} expressing the throughput of the fluid system as a piecewise linear function of the resources, revealing the existence of different congestion phases. Numerical experiments show that the analysis of the fluid dynamics yields a good approximation of the real throughput.Comment: 21 pages, 4 figures. A shorter version can be found in the proceedings of the conference FORMATS 201

Fluid-flow solutions in PEPA to the state space explosion problem

Achieving the appropriate performance requirements for computer-communication systems is as important as the correctness of the end-result. This is particularly difficult in the case of massively parallel computer systems such as the clusters of PCs behind the likes of Google and peer-to-peer filesharing networks such as Bittorrent. Measuring the performance of such systems using a mathematical model is invariably computationally intensive. Formal modelling techniques make possible the derivation of such performance measures but currently suffer from the state-space explosion problem, that is, models become intractably large even for systems of apparently modest complexity. This work develops a novel class of techniques aimed at addressing this problem by approximating a representation of massive state spaces as more computationally-tractable real variables (fluid-flow analysis)