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
The advantages of the compositional structure within PEPA for model construction and simplification ...
. We introduce a Stochastic Process Algebra called PEPA 1 ph , based on Hillston's PEPA. PEPA...
Abstract Fluid or mean-field methods are approximate analytical techniques which have proven effecti...
AbstractIn this paper we examine a Langevin interpretation of the stochastic process algebra PEPA. W...
The exact performance analysis of large-scale software systems with discrete-state approaches is dif...
In this tutorial we give an introduction to stochastic process algebras and their use in performance...
AbstractMarkovian process algebras, such as PEPA and stochastic π-calculus, bring a powerful composi...
Stochastic process algebras such as PEPA have enjoyed considerable success as CTMC-based system desc...
Abstract. In this chapter we introduce process algebras, a class of for-mal modelling techniques dev...
Abstract: In the study of stochastic process algebra it is necessary to consider not only how system...
Stochastic process algebras have become an accepted part of performance modelling over recent years....
Stochastic process algebras have become an accepted part of performance modelling over recent years....
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...
The performance modelling of large-scale systems using discrete-state approaches is fundamentally ha...
The advantages of the compositional structure within PEPA for model construction and simplification ...
. We introduce a Stochastic Process Algebra called PEPA 1 ph , based on Hillston's PEPA. PEPA...
Abstract Fluid or mean-field methods are approximate analytical techniques which have proven effecti...
AbstractIn this paper we examine a Langevin interpretation of the stochastic process algebra PEPA. W...
The exact performance analysis of large-scale software systems with discrete-state approaches is dif...
In this tutorial we give an introduction to stochastic process algebras and their use in performance...
AbstractMarkovian process algebras, such as PEPA and stochastic π-calculus, bring a powerful composi...
Stochastic process algebras such as PEPA have enjoyed considerable success as CTMC-based system desc...
Abstract. In this chapter we introduce process algebras, a class of for-mal modelling techniques dev...
Abstract: In the study of stochastic process algebra it is necessary to consider not only how system...
Stochastic process algebras have become an accepted part of performance modelling over recent years....
Stochastic process algebras have become an accepted part of performance modelling over recent years....
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...
The performance modelling of large-scale systems using discrete-state approaches is fundamentally ha...
The advantages of the compositional structure within PEPA for model construction and simplification ...
. We introduce a Stochastic Process Algebra called PEPA 1 ph , based on Hillston's PEPA. PEPA...
Abstract Fluid or mean-field methods are approximate analytical techniques which have proven effecti...