Passage-End Analysis

Abstract. Passage-end calculations are a new style of passage measurement for eXtended Stochastic Probes (XSP) [1] which add the ability to split the analysis into several cases depending on conditions which hold at the end of a passage. This makes it possible to separate successful responses to a request from negative responses, timeouts or other failures. This allows the expression of service level agreements such as: “At least 90 percent of all requests receive a response within 10 seconds and at least 60 percent of all such requests are successful.”

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

Scalable Analysis of Scalable Systems

Abstract. We present a systematic method of analysing the scalability of large-scale systems. We construct a high-level model using the SRMC process calculus and generate variants of this using model transformation. The models are compiled into systems of ordinary differential equations and numerically integrated to predict non-functional properties such as responsiveness and scalability.

Service-Level Agreements for Service-Oriented Computing

Abstract. Service-oriented computing is dynamic. There may be many possible service instances available for binding, leading to uncertainty about where service requests will execute. We present a novel Markovian process calculus which allows the formal expression of uncertainty about binding as found in service-oriented computing. We show how to compute meaningful quantitative information about the quality of service provided in such a setting. These numerical results can be used to allow the expression of accurate service-level agreements about service-oriented computing.

Sensoria Patterns: Augmenting Service Engineering with Formal Analysis, Transformation and Dynamicity

The IST-FET Integrated Project Sensoria is developing a novel comprehensive approach to the engineering of service-oriented software systems where foundational theories, techniques and methods are fully integrated into pragmatic software engineering processes. The techniques and tools of Sensoria encompass the whole software development cycle, from business and architectural design, to quantitative and qualitative analysis of system properties, and to transformation and code generation. The Sensoria approach takes also into account reconfiguration of service-oriented architectures (SOAs) and re-engineering of legacy systems. In this paper we give first a short overview of Sensoria and then present a pattern language for augmenting service engineering with formal analysis, transformation and dynamicity. The patterns are designed to help software developers choose appropriate tools and techniques to develop service-oriented systems with support from formal methods. They support the whole development process, from the modelling stage to deployment activities and give an overview of many of the research areas pursued in the Sensoria project

Studying the effects of adding spatiality to a process algebra model

We use NetLogo to create simulations of two models of disease transmission originally expressed in WSCCS. This allows us to introduce spatiality into the models and explore the consequences of having different contact structures among the agents. In previous work, mean field equations were derived from the WSCCS models, giving a description of the aggregate behaviour of the overall population of agents. These results turned out to differ from results obtained by another team using cellular automata models, which differ from process algebra by being inherently spatial. By using NetLogo we are able to explore whether spatiality, and resulting differences in the contact structures in the two kinds of models, are the reason for this different results. Our tentative conclusions, based at this point on informal observations of simulation results, are that space does indeed make a big difference. If space is ignored and individuals are allowed to mix randomly, then the simulations yield results that closely match the mean field equations, and consequently also match the associated global transmission terms (explained below). At the opposite extreme, if individuals can only contact their immediate neighbours, the simulation results are very different from the mean field equations (and also do not match the global transmission terms). These results are not surprising, and are consistent with other cellular automata-based approaches. We found that it was easy and convenient to implement and simulate the WSCCS models within NetLogo, and we recommend this approach to anyone wishing to explore the effects of introducing spatiality into a process algebra model

The SENSORIA reference modelling language

This chapter provides an overview of SRML - the Sensoria Reference Modelling Language. Our focus will be on the language primitives that SRML offers for modelling business services and activities, the methodological approach that SRML supports, and the mathematical semantics the underpins the modelling approach, including techniques for qualitative and quantitative analysis. © 2011 Springer-Verlag Berlin Heidelberg

Scalable analysis of stochastic process algebra models

The performance modelling of large-scale systems using discrete-state approaches is fundamentally hampered by the well-known problem of state-space explosion, which causes exponential growth of the reachable state space as a function of the number of the components which constitute the model. Because they are mapped onto continuous-time Markov chains (CTMCs), models described in the stochastic process algebra PEPA are no exception. This thesis presents a deterministic continuous-state semantics of PEPA which employs ordinary differential equations (ODEs) as the underlying mathematics for the performance evaluation. This is suitable for models consisting of large numbers of replicated components, as the ODE problem size is insensitive to the actual population levels of the system under study. Furthermore, the ODE is given an interpretation as the fluid limit of a properly defined CTMC model when the initial population levels go to infinity. This framework allows the use of existing results which give error bounds to assess the quality of the differential approximation. The computation of performance indices such as throughput, utilisation, and average response time are interpreted deterministically as functions of the ODE solution and are related to corresponding reward structures in the Markovian setting. The differential interpretation of PEPA provides a framework that is conceptually analogous to established approximation methods in queueing networks based on meanvalue analysis, as both approaches aim at reducing the computational cost of the analysis by providing estimates for the expected values of the performance metrics of interest. The relationship between these two techniques is examined in more detail in a comparison between PEPA and the Layered Queueing Network (LQN) model. General patterns of translation of LQN elements into corresponding PEPA components are applied to a substantial case study of a distributed computer system. This model is analysed using stochastic simulation to gauge the soundness of the translation. Furthermore, it is subjected to a series of numerical tests to compare execution runtimes and accuracy of the PEPA differential analysis against the LQN mean-value approximation method. Finally, this thesis discusses the major elements concerning the development of a software toolkit, the PEPA Eclipse Plug-in, which offers a comprehensive modelling environment for PEPA, including modules for static analysis, explicit state-space exploration, numerical solution of the steady-state equilibrium of the Markov chain, stochastic simulation, the differential analysis approach herein presented, and a graphical framework for model editing and visualisation of performance evaluation results