Stochastic Approximation of Global Reachability Probabilities of Markov Population Models
| Autor: | Roberta Lanciani, Luca Bortolussi |
|---|---|
| Přispěvatelé: | Horvat, A., Wolter, K., Bortolussi, Luca, Roberta, Lanciani |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Mathematical optimization
Stochastic Approximation Computation Markov process 0102 computer and information sciences 02 engineering and technology Stochastic approximation 01 natural sciences symbols.namesake Reachability Reachability Probability 0202 electrical engineering electronic engineering information engineering State space hitting times Mathematics Central limit theorem Markov chain Stochastic Model Checking 010201 computation theory & mathematics Bounded function central limit approximation symbols 020201 artificial intelligence & image processing Markov Population Models reachability |
| Zdroj: | Computer Performance Engineering ISBN: 9783319108841 EPEW EPEW 2014-Computer Performance Engineering. 11th European Workshop, pp. 224–239, Florence, Italy, 11-12 September 2014 info:cnr-pdr/source/autori:Bortolussi L.; Lanciani R./congresso_nome:EPEW 2014-Computer Performance Engineering. 11th European Workshop/congresso_luogo:Florence, Italy/congresso_data:11-12 September 2014/anno:2014/pagina_da:224/pagina_a:239/intervallo_pagine:224–239 |
| Popis: | Complex computer systems, from peer-to-peer networks to the spreading of computer virus epidemics, can often be described as Markovian models of large populations of interacting agents. Many properties of such systems can be rephrased as the computation of time bounded reachability probabilities. However, large population models suffer severely from state space explosion, hence a direct computation of these probabilities is often unfeasible. In this paper we present some results in estimating these probabilities using ideas borrowed from Fluid and Central Limit approximations. We consider also an empirical improvement of the basic method leveraging higher order stochastic approximations. Results are illustrated on a peer-to-peer example. © 2014 Springer International Publishing. |
| Databáze: | OpenAIRE |
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