Analyse du processus d'élaboration d'un projet de simulation

International audienceNous présentons dans cet article une étude orientée sur l'analyse du processus d'élaboration d'un projet de simulation de système de production. Après avoir présenté un état de l'art traitant de cette problématique, nous détaillons le cadre d'élaboration d'un processus de simulation à travers la présentation des différentes étapes le constituant ainsi que celle des délivrables qui lui sont associés. Nous donnons ainsi la vision que nous avons de ce processus. L'accent est en particulier mis sur le rôle déterminant de la première étape qui vise à identifier et caractériser le besoin à l'origine du projet de simulation, généralement un problème à résoudre, et à évaluer la capacité de l'outil de simulation à évènements discrets à répondre efficacement à ce besoin. Nous proposons ensuite une classification des outils de simulation actuellement présents sur le marché en fonction de l'approche de modélisation utilisée, à savoir les outils orientés " fonction " ou " processus " et les outils orientés " composant " ou " objet ". Ainsi, après une description assez brève de ces approches de modélisation, nous présentons certains des avantages et des inconvénients de chaque type d'outil par rapport à un point de vue de l'utilisateur potentiel

A Case Study on Grid Performance Modeling

The purpose of this case study is to develop a performance model for an enterprise grid for performance management and capacity planning1. The target environment includes grid applications such as health-care and financial services where the data is located primarily within the resources of a worldwide corporation. The approach is to build a discrete event simulation model for a representative work-flow grid. Five work-flow classes, found using a customized k-means clustering algorithm characterize the workload of the grid. Analyzing the gap between the simulation and measurement data validates the model. The case study demonstrates that the simulation model can be used to predict the grid system performance given a workload forecast. The model is also used to evaluate alternative scheduling strategies. The simulation model is flexible and easily incorporates several system details

Surface steps dominate the water formation on Pd(111) surfaces

Water formation is relevant in many technological processes and is also an important model reaction. Although water formation over Pd surfaces is widely studied, questions regarding the active site and the main reaction path (OH* + OH*) or (OH* + H*) are still open. Combining first-principles density functional theory calculations and kinetic Monte Carlo simulations, we find that the reaction rate is dominated by surface steps and point defects over a wide range of conditions. The main reaction path is found to be temperature dependent where the OH* + OH* path dominates at low temperatures, whereas the OH* + H* path is the main path at high temperatures. Steps facilitate the OH* formation, which is the rate limiting step under all conditions. OH* is formed via O* + H* association or OOH* splitting at low temperatures, whereas OH* is exclusively formed via O* + H* association at high temperatures. The results of the first-principles-based kinetic model are in excellent agreement with experimental observations at high and low temperatures as well as different gas-phase compositions

Stochastic simulation of event structures

Currently the semantics of stochastic process algebras are defined using (an extension) of labelled transition systems. This usually results in a semantics based on the interleaving of causally independent actions. The advantage is that the structure of transition systems closely resembles that of Markov chains, enabling the use of standard solution techniques for analytical and numerical performance assessment of formal specifications. The main drawback is that distributions are restricted to be exponential. In [2] we proposed to use a partial-order semantics for stochastic process algebras. This allows the support of non-exponential distributions in the process algebra in a perspicuous way, but the direct resemblance with Markov chains is lost. This paper proposes to exploit discrete-event simulation techniques for analyzing our partial-order model, called stochastic event structures. The key idea is to obtain from event structures so-called (time-homogeneous) generalized semiMarkov ..

Probabilistic Performance Testing of Web Applications

IT süsteemid muutuvad oma elutsükli vältel järjest keerulisemaks. Veebirakendusi kasutatakse eriti laialt erinevatel eesmärkidel, sest võrgupõhine juurdepääs informatsioonile on väga mugav. Kuid võrgupõhise juurdepääsu juures tekivad mõned probleemid, mida tuleks silmas pidada. Kasutajad eeldavad prognoositavat jõudlust (nt nõuetekohane reaktsiooniaeg), seega teenusepakkujad peavad teadma, kuidas nende süsteem töötab erinevate koormuste all. Selles teesis loome tõhususe analüütilise mudeli ja töötame välja programmi, mis selle lahendab. Antud programm lubab analüüsida veebirakenduste jõudlust ja vastata järgmistele küsimustele: 1)missugune on keskmine süsteemi reaktsiooniaeg? 2)missugune on süsteemi kasutamine üldiselt? Parameetrid programmi jaoks nagu keskmine teenindusaeg, uute taotluste keskmine saabumisaeg, keskmine mõtlemisaeg, on saadud testsüsteemi reaalse koormuse logidest. Jõudluse mudel on välja töötatud Queuing Networksi abil, mis lubab analüüsida süsteemi matemaatiliste valemite abil.Web systems are used widely for reaching different purposes, as remote access to information is very convenient. However, the remote access brings many aspects which should be handled. Users expect predictable performance levels (e.g., acceptable response time), therefore, service providers should know how their system performs under different loading conditions. In this thesis I design an analytical performance model and develop a tool which can solve that model. The tool allows analyzing the performance of web applications and answer the following questions: 1)What is the average response time of the system? 2)What is the utilization of the system as a whole? The input parameters, such as the average service time of transactions, average arrival rate of requests, and the average think time, are estimated from a real workload (of a system under test). The performance model is developed by means of Queuing Networks, a framework which enables the analysis of a system in terms of mathematical formula

Two-Stage Estimation of Non-Recursive Choice Models

Questions of causation are important issues in empirical research on political behavior. Most of the discussion of the econometric problems associated with multi-equation models with reciprocal causation has focused on models with continuous dependent variables (e.g. Markus and Converse 1979; Page and Jones 1979). Since many models of political behavior involve discrete or dichotomous dependent variables, this paper turns to two techniques which can be employed to estimate reciprocal relationships between dichotomous and continuous dependent variables. One technique which I call two-stage probit least squares (2SPLS) is very similar to familiar two-stage instrumental variable techniques. The second technique, called two-stage conditional maximum likelihood (2SCML), may overcome problems associated with 2SPLS, but has not been used in the political science literature. First I show the properties of both techniques using Monte Carlo simulations. Then, I apply these techniques to an empirical example which focuses on the relationship between voter preferences in a presidential election and the voter's uncertainty about the policy positions taken by the candidates. This example demonstrates the importance of these techniques for political science research