Fluid flow approximation allows efficient analysis of large scale PEPA models. Given a model, this method outputs how the mean, variance, and any other moment of the model's stochastic behaviour evolves as a function of time. We investigate whether the method's results, i.e. moments of the behaviour, are sufficient to capture system's actual dynamics. We ran a series of experiments on a client-server model. For some parametrizations of the model, the model's behaviour can accurately be characterized by the fluid flow approximations of its moments. However, the experiments show that for some other parametrizations, these moments are not sufficient to capture the model's behaviour, highlighting a pitfall of relying only on the results of flu...
In this paper we consider the use of a fluid flow approximation based on ordinary differential equat...
Emergent phenomena occur due to the pattern of non-linear and distributed local interactions between...
Layered queueing networks are a useful tool for the performance modeling and prediction of software ...
We present an application of partial evaluation to performance models expressed in the PEPA stochast...
Performance Evaluation Process Algebra (PEPA) [1] is fifteen years old this year. This talk will sur...
In this paper we show how the powerful ODE-based fluid-analysis technique for the stochastic process...
The fluid interpretation of the process calculus PEPA provides a very useful tool for the performanc...
AbstractMarkovian process algebras, such as PEPA and stochastic π-calculus, bring a powerful composi...
Achieving the appropriate performance requirements for computer-communication systems is as importan...
Reasoning about the performance of models of software systems typically entails the derivation of me...
We review several developments in fluid flow models: feedback fluid models, linear stochastic fluid ...
Stochastic fluid models have been applied to model and evaluate the performance of many important re...
The stochastic process algebra PEPA is a powerful modelling formalism for concurrent systems, which...
AbstractRecent developments in the analysis of large Markov models facilitate the fast approximation...
Simulating fluid motion accurately and robustly is an enduring problem due to the com- plexity and c...
In this paper we consider the use of a fluid flow approximation based on ordinary differential equat...
Emergent phenomena occur due to the pattern of non-linear and distributed local interactions between...
Layered queueing networks are a useful tool for the performance modeling and prediction of software ...
We present an application of partial evaluation to performance models expressed in the PEPA stochast...
Performance Evaluation Process Algebra (PEPA) [1] is fifteen years old this year. This talk will sur...
In this paper we show how the powerful ODE-based fluid-analysis technique for the stochastic process...
The fluid interpretation of the process calculus PEPA provides a very useful tool for the performanc...
AbstractMarkovian process algebras, such as PEPA and stochastic π-calculus, bring a powerful composi...
Achieving the appropriate performance requirements for computer-communication systems is as importan...
Reasoning about the performance of models of software systems typically entails the derivation of me...
We review several developments in fluid flow models: feedback fluid models, linear stochastic fluid ...
Stochastic fluid models have been applied to model and evaluate the performance of many important re...
The stochastic process algebra PEPA is a powerful modelling formalism for concurrent systems, which...
AbstractRecent developments in the analysis of large Markov models facilitate the fast approximation...
Simulating fluid motion accurately and robustly is an enduring problem due to the com- plexity and c...
In this paper we consider the use of a fluid flow approximation based on ordinary differential equat...
Emergent phenomena occur due to the pattern of non-linear and distributed local interactions between...
Layered queueing networks are a useful tool for the performance modeling and prediction of software ...