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Applying Mean-field Approximation to Continuous Time Markov Chains

Kolesnichenko, Anna and Pourranjabar, Alireza and Senni, Valerio Applying Mean-field Approximation to Continuous Time Markov Chains. CSA Technical Report #8/2013 IMT Institute for Advanced Studies Lucca

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The mean-field analysis technique is used to perform analysis of a systems with a large number of components to determine the emergent deterministic behaviour and how this behaviour modifies when its parameters are perturbed. The computer science performance modelling and analysis community has found the mean-field method useful for modelling large-scale computer and communication networks. Applying mean-field analysis from the computer science perspective requires the following major steps: (1) describing how the agents populations evolve by means of a system of differential equations, (2) finding the emergent deterministic behaviour of the system by solving such differential equations, and (3) analysing properties of this behaviour either by relying on simulation or by using logics. Depending on the system under analysis, performing these steps may become challenging. Often, modifications of the general idea are needed. In this tutorial we consider illustrating examples to discuss how the mean-field method is used in different application areas. Starting from the application of the classical technique, moving to cases where additional steps have to be used, such as systems with local communication. Finally we illustrate the application of the simulation and uid model checking analysis techniques.

Item Type: Working Paper (CSA Technical Report)
Uncontrolled Keywords: Continuous Time Markov Chains; Mean-field Approximation; Performance Analysis; Model Checking
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Research Area: Computer Science and Applications
Depositing User: Ms T. Iannizzi
Date Deposited: 20 Jun 2013 08:03
Last Modified: 20 Jun 2013 08:03
URI: http://eprints.imtlucca.it/id/eprint/1620

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