211 research outputs found
An Aggregation Technique for Large-Scale PEPA Models with Non-Uniform Populations
Performance analysis based on modelling consists of two major steps: model
construction and model analysis. Formal modelling techniques significantly aid
model construction but can exacerbate model analysis. In particular, here we
consider the analysis of large-scale systems which consist of one or more
entities replicated many times to form large populations. The replication of
entities in such models can cause their state spaces to grow exponentially to
the extent that their exact stochastic analysis becomes computationally
expensive or even infeasible.
In this paper, we propose a new approximate aggregation algorithm for a class
of large-scale PEPA models. For a given model, the method quickly checks if it
satisfies a syntactic condition, indicating that the model may be solved
approximately with high accuracy. If so, an aggregated CTMC is generated
directly from the model description. This CTMC can be used for efficient
derivation of an approximate marginal probability distribution over some of the
model's populations. In the context of a large-scale client-server system, we
demonstrate the usefulness of our method
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.
Fluid Model Checking
In this paper we investigate a potential use of fluid approximation
techniques in the context of stochastic model checking of CSL formulae. We
focus on properties describing the behaviour of a single agent in a (large)
population of agents, exploiting a limit result known also as fast simulation.
In particular, we will approximate the behaviour of a single agent with a
time-inhomogeneous CTMC which depends on the environment and on the other
agents only through the solution of the fluid differential equation. We will
prove the asymptotic correctness of our approach in terms of satisfiability of
CSL formulae and of reachability probabilities. We will also present a
procedure to model check time-inhomogeneous CTMC against CSL formulae
Amalgamation of Transition Sequences in the PEPA Formalism
This report presents a proposed formal approach towards reduction of sequences in PEPA components. By performing the described amalgamation procedure we may remove, from the Markov chain underlying an initial PEPA model, those states for which detailed local balance equations cannot be formulated. This transformation may lead to a simpler model with product form solution. Some classes of reduced models preserve those performance measures which we are interested in and, moreover, the steady state solution vector is much easier to find from the computational point of view
Population models from PEPA descriptions
Stochastic process algebras such as PEPA have enjoyed considerable success as CTMC-based system description languages for performance evaluation of computer and communication systems. However they have not been able to escape the problem of state space explosion, and this problem is exacerbated when other domains such as systems biology are considered. Therefore we have been investigating alternative semantics for PEPA models which give rise to a population view of the system, in terms of a set of nonlinear ordinary differential equations. This extended abstract gives an overview of this mapping
Hybrid performance modelling of opportunistic networks
We demonstrate the modelling of opportunistic networks using the process
algebra stochastic HYPE. Network traffic is modelled as continuous flows,
contact between nodes in the network is modelled stochastically, and
instantaneous decisions are modelled as discrete events. Our model describes a
network of stationary video sensors with a mobile ferry which collects data
from the sensors and delivers it to the base station. We consider different
mobility models and different buffer sizes for the ferries. This case study
illustrates the flexibility and expressive power of stochastic HYPE. We also
discuss the software that enables us to describe stochastic HYPE models and
simulate them.Comment: In Proceedings QAPL 2012, arXiv:1207.055
HYPE with stochastic events
The process algebra HYPE was recently proposed as a fine-grained modelling
approach for capturing the behaviour of hybrid systems. In the original
proposal, each flow or influence affecting a variable is modelled separately
and the overall behaviour of the system then emerges as the composition of
these flows. The discrete behaviour of the system is captured by instantaneous
actions which might be urgent, taking effect as soon as some activation
condition is satisfied, or non-urgent meaning that they can tolerate some
(unknown) delay before happening. In this paper we refine the notion of
non-urgent actions, to make such actions governed by a probability
distribution. As a consequence of this we now give HYPE a semantics in terms of
Transition-Driven Stochastic Hybrid Automata, which are a subset of a general
class of stochastic processes termed Piecewise Deterministic Markov Processes.Comment: In Proceedings QAPL 2011, arXiv:1107.074
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