514 research outputs found
Specifying Performance Measures for PEPA
Abstract. Stochastic process algebras such as PEPA provide ample support for the component-based construction of models. Tools compute the numerical solution of these models; however, the stochastic process algebra methodology lacks support for the specification and calculation of complex performance measures. This paper addresses that problem by presenting a performance specification language which supports high level reasoning about PEPA models, allowing the description of equilibrium (steady-state) measures. The meaning of the specification language can be made formal by examining its foundations in a stochastic modal logic. A case-study is presented to illustrate the approach.
A survey of the PEPA tools
This paper surveys the history and the current state of tool support for modelling with the PEPA stochastic process algebra and the PEPA nets modelling language. We discuss future directions for tool support for the PEPA family of languages.
A new tool for the performance analysis of massively parallel computer systems
We present a new tool, GPA, that can generate key performance measures for
very large systems. Based on solving systems of ordinary differential equations
(ODEs), this method of performance analysis is far more scalable than
stochastic simulation. The GPA tool is the first to produce higher moment
analysis from differential equation approximation, which is essential, in many
cases, to obtain an accurate performance prediction. We identify so-called
switch points as the source of error in the ODE approximation. We investigate
the switch point behaviour in several large models and observe that as the
scale of the model is increased, in general the ODE performance prediction
improves in accuracy. In the case of the variance measure, we are able to
justify theoretically that in the limit of model scale, the ODE approximation
can be expected to tend to the actual variance of the model
Analysis of a Multimedia Stream using Stochastic Process Algebra
It is now well recognised that the next generation of distributed systems will be distributed multimedia systems. Central to multimedia systems is quality of service, which defines the non-functional requirements on the system. In this paper we investigate how stochastic process algebra can be used in order to determine the quality of service properties of distributed multimedia systems. We use a simple multimedia stream as our basic example. We describe it in the Stochastic Process Algebra PEPA and then we analyse whether the stream satisfies a set of quality of service parameters: throughput, end-to-end latency, jitter and error rates
Fluid passage-time calculation in large Markov models
Recent developments in the analysis of large Markov models facilitate the fast approximation of transient characteristics of the underlying stochastic process. So-called fluid analysis makes it possible to consider previously intractable models whose underlying discrete state space grows exponentially as model components are added. In this work, we show how fluid approximation techniques may be used to extract passage-time measures from performance models. We focus on two types of passage measure: passage-times involving individual components; as well as passage-times which capture the time taken for a population of components to evolve. Specifically, we show that for models of sufficient scale, passage-time distributions can be well approximated by a deterministic fluid-derived passage-time measure. Where models are not of sufficient scale, we are able to generate approximate bounds for the entire cumulative distribution function of these passage-time random variables, using moment-based techniques. Finally, we show that for some passage-time measures involving individual components the cumulative distribution function can be directly approximated by fluid techniques
Rate-Based Transition Systems for Stochastic Process Calculi
A variant of Rate Transition Systems (RTS), proposed by Klin and Sassone, is introduced and used as the basic model for defining stochastic behaviour of processes. The transition relation used in our variant associates to each process, for each action, the set of possible futures paired with a measure indicating their rates. We show how RTS can be used for providing the operational semantics of stochastic extensions of classical formalisms, namely CSP and CCS. We also show that our semantics for stochastic CCS guarantees associativity of parallel composition. Similarly, in contrast with the original definition by Priami, we argue that a semantics for stochastic Ļ-calculus can be provided that guarantees associativity of parallel composition
Complementary approaches to understanding the plant circadian clock
Circadian clocks are oscillatory genetic networks that help organisms adapt
to the 24-hour day/night cycle. The clock of the green alga Ostreococcus tauri
is the simplest plant clock discovered so far. Its many advantages as an
experimental system facilitate the testing of computational predictions.
We present a model of the Ostreococcus clock in the stochastic process
algebra Bio-PEPA and exploit its mapping to different analysis techniques, such
as ordinary differential equations, stochastic simulation algorithms and
model-checking. The small number of molecules reported for this system tests
the limits of the continuous approximation underlying differential equations.
We investigate the difference between continuous-deterministic and
discrete-stochastic approaches. Stochastic simulation and model-checking allow
us to formulate new hypotheses on the system behaviour, such as the presence of
self-sustained oscillations in single cells under constant light conditions.
We investigate how to model the timing of dawn and dusk in the context of
model-checking, which we use to compute how the probability distributions of
key biochemical species change over time. These show that the relative
variation in expression level is smallest at the time of peak expression,
making peak time an optimal experimental phase marker. Building on these
analyses, we use approaches from evolutionary systems biology to investigate
how changes in the rate of mRNA degradation impacts the phase of a key protein
likely to affect fitness. We explore how robust this circadian clock is towards
such potential mutational changes in its underlying biochemistry. Our work
shows that multiple approaches lead to a more complete understanding of the
clock
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