Cluster Grid based Response-time analysis module for the PIPE Tool.

Generalized Stochastic Petri Nets (GSPNs) are a widely used high-level formalism used for modelling discrete-event systems. The Platform Independent Petri net Editor (PIPE) is an open source software project that allows creation, analysis and simulation of Petri Nets. This tool paper presents a PIPE module for response-time analysis of a Petri net’s underlying Continuous Time Markov Chain (CTMC). Jobs are submitted via a web interface, from within PIPE or from a browser. The parallel computations are run using Grid Engine on a cluster hosted at Imperial College London. 1

Exploration of the network spun by website users

Using data stretching over more than 5 years for the website http://gallery.future-i.com/ this paper investigates basic properties of the popularity of pictures and the way users navigate through the website. We find that the rank frequency plot of the downloaded pictures follows a Zipf law. The download rate of individual popular pictures over time resembles that seen of infection rates of diseases. The graph created by successive downloads of pictures shows a power law that does not change over different time periods. We discuss how our findings can be modelled and how they are of importance to website performance

Location-Aware Quality of Service Measurements for Service-Level Agreements

We add specifications of location-aware measurements to performance models in a compositional fashion, promoting precision in performance measurement design. Using immediate actions to send control signals between measurement components we are able to obtain more accurate measurements from our stochastic models without disturbing their structure. A software tool processes both the model and the measurement specifications to give response time distributions and quantiles, an essential calculation in determining satisfaction of service-level agreements (SLAs)

How Synchronisation Strategy Approximation in PEPA Implementations Affects Passage Time Performance Results

Abstract. Passage time densities are useful performance measurements in stochastic systems. With them the modeller can extract probabilistic quality-of-service guarantees such as: the probability that the time taken for a network header packet to travel across a heterogeneous network is less than 10ms must be at least 0.95. In this paper, we show how new tools can extract passage time densities and distributions from stochastic models defined in PEPA, a stochastic process algebra. In stochastic process algebras, the synchronisation policy is important for defining how different system components interact. We also show how these passage time results can vary according to which synchronisation strategy is used. We compare results from two popular strategies.

Data as processes: introducing measurement data into CARMA models

Measurement data provides a precise and detailed description of components within a complex system but it is rarely used directly as a component of a system model. In this paper we introduce a model-based representation of measurement data and use it together with modeller-defined components expressed in the CARMA modelling language. We assess both liveness and safety properties of these models with embedded data.Comment: In Proceedings FORECAST 2016, arXiv:1607.0200

Stochastic Simulation Methods Applied to a Secure Electronic Voting Model

We demonstrate a novel simulation technique for analysing large stochastic process algebra models, applying this to a secure electronic voting system example. By approximating the discrete state space of a PEPA model by a continuous equivalent, we can draw on rate equation simulation techniques from both chemical and biological modelling to avoid having to directly enumerate the huge state spaces involved. We use stochastic simulation techniques to provide traces of course-of-values time series representing the number of components in a particular state. Using such a technique we can get simulation results for models exceeding 10 10000 states within only a few seconds

A Continuous State Space Approximation for PEPA Queues

PEPA Queues is a formalism that augments queueing networks with customers that have behavioural characteristics, as defined by PEPA components. PEPA Queues suffer from the traditional state-space explosion that affects both closed queueing networks and PEPA models. We discuss a possible solution to this with a continuous state-space approximation that allows us to derive an underlying mathematical model based on ordinary differential equations from a PEPA Queues model.

24th UK performance engineering workshop

Departmental Technical Report: 08/