AbstractIn this paper we examine a Langevin interpretation of the stochastic process algebra PEPA. We show how previous work on chemical systems yielding sets of stochastic differential equations (SDEs) can be adapted to the domain of computer systems. Two simple examples are then examined. Their experimental results show a good match between traditional Markovian interpretation of PEPA and the SDE interpretation introduced here. It also raises the problem of boundary conditions which is briefly discussed and for which we propose a solution
grant no. 95306547The performance modeller may attempt to quantitatively analyse the behaviour of co...
In order to circumvent the problem of state-space explosion of large-scale Markovian models, the sto...
In order to circumvent the problem of state-space explosion of large-scale Markovian models, the sto...
AbstractIn this paper we examine a Langevin interpretation of the stochastic process algebra PEPA. W...
Stochastic process algebras such as PEPA have enjoyed considerable success as CTMC-based system desc...
The performance modelling of large-scale systems using discrete-state approaches is fundamentally h...
AbstractMarkovian process algebras, such as PEPA and stochastic π-calculus, bring a powerful composi...
The Chemical Langevin Equation (CLE), which is a stochastic differential equation (SDE) driven by a ...
The exact performance analysis of large-scale software systems with discrete-state approaches is dif...
Abstract Fluid or mean-field methods are approximate analytical techniques which have proven effecti...
The stochastic process algebra PEPA is a powerful modelling formalism for concurrent systems, which...
Markov chains offer a rigorous mathematical framework to describe systems that exhibit stochastic b...
Stochastic process algebras have become an accepted part of performance modelling over recent years....
In this tutorial we give an introduction to stochastic process algebras and their use in performance...
Stochastic process algebras have become an accepted part of performance modelling over recent years....
grant no. 95306547The performance modeller may attempt to quantitatively analyse the behaviour of co...
In order to circumvent the problem of state-space explosion of large-scale Markovian models, the sto...
In order to circumvent the problem of state-space explosion of large-scale Markovian models, the sto...
AbstractIn this paper we examine a Langevin interpretation of the stochastic process algebra PEPA. W...
Stochastic process algebras such as PEPA have enjoyed considerable success as CTMC-based system desc...
The performance modelling of large-scale systems using discrete-state approaches is fundamentally h...
AbstractMarkovian process algebras, such as PEPA and stochastic π-calculus, bring a powerful composi...
The Chemical Langevin Equation (CLE), which is a stochastic differential equation (SDE) driven by a ...
The exact performance analysis of large-scale software systems with discrete-state approaches is dif...
Abstract Fluid or mean-field methods are approximate analytical techniques which have proven effecti...
The stochastic process algebra PEPA is a powerful modelling formalism for concurrent systems, which...
Markov chains offer a rigorous mathematical framework to describe systems that exhibit stochastic b...
Stochastic process algebras have become an accepted part of performance modelling over recent years....
In this tutorial we give an introduction to stochastic process algebras and their use in performance...
Stochastic process algebras have become an accepted part of performance modelling over recent years....
grant no. 95306547The performance modeller may attempt to quantitatively analyse the behaviour of co...
In order to circumvent the problem of state-space explosion of large-scale Markovian models, the sto...
In order to circumvent the problem of state-space explosion of large-scale Markovian models, the sto...