PEPA has a long history of software tool support. As we saw in the lecture note, the PEPA Eclipse Plug-in has been recently proposed as an implementation of the language which supports the whole model development process with a rich graphical interface. Lecture note 14 provided an overview of the main plug-in features such as static analysis and numerical solution of the underlying continuous-t...

Model Checking Markov Chains Markov chains are widely used for modelling the behaviour of computer and communication systems. A common goal of modelling is the estimation of performance and dependability measures of the system under study, such as throughput, buffer occupancy or mean time to failure. With model checking, the angle is somewhat different: Instead of conducting an analysis whose a...

The Performance Evaluation Process Algebra (PEPA) language is a stochastic process algebra, generating Continuous Time Markov Chains (CTMC) to allow quantitative analysis. Protocols such as BitTorrent are highly parallel in nature, and represent one area where CTMC analysis is limited by the well-known state space problem. The number of unique states each client can exist in, and the number of ...

In cognitive radio networks, channel aggregation (CA) and channel fragmentation (CF) techniques have been proposed to enhance the spectrum utilization. While most of the literature studies CA and CF independently, in this paper we combine CA and CF innovatively and present a new spectrum sharing strategy named CAF (Channel Aggregation and Fragmentation). We elaborate on the proposed CAF strateg...

A Markovian Agent Model (MAM) is a stochastic model that provides a flexible, powerful and scalable way for analyzing complex systems of distributed interacting objects. The constituting bricks of a MAM are the Markovian Agents (MA) represented by a finite state continuous time Markov chain (CTMC) whose infinitesimal generator is composed by a fixed component (the local behaviour) and an induce...

In this paper, we propose a distributed channel allocation scheme for the uplink data traffic and implement a priority oriented scheduling for the downlink data traffic for a powerline access type network. We study the performance of the uplink and downlink protocols in terms of the buffering probability, mean delay, statistical dropping probability and the number of subscriber stations support...

Degradable fault-tolerant systems can be evaluated using rewarded continuous-time Markov chain (CTMC) models. In that context, a useful measure to consider is the distribution of the cumulative reward over a time interval [0, t]. All currently available numerical methods for computing that measure tend to be very expensive when the product of the maximum output rate of the CTMC model and t is l...