The Evolution of Jolie: From Orchestrations to Adaptable Choreographies

International audienceJolie is an orchestration language conceived during Sensoria, an FP7 European project led by Martin Wirsing in the time frame 2005– 2010. Jolie was designed having in mind both the novel –at project time– concepts related to Service-Oriented Computing and the traditional approach to the modelling of concurrency typical of process calculi. The foundational work done around Jolie during Sensoria has subsequently produced many concrete results. In this paper we focus on two distinct advancements, one aiming at the development of dynamically adaptable orchestrated systems and one focusing on global choreographic specifications. These works, more recently, contributed to the realisation of a framework for programming dynamically evolvable distributed Service-Oriented applications that are correct-by-construction

Scalable Performance Analysis of Massively Parallel Stochastic Systems

The accurate performance analysis of large-scale computer and communication systems is directly inhibited by an exponential growth in the state-space of the underlying Markovian performance model. This is particularly true when considering massively-parallel architectures such as cloud or grid computing infrastructures. Nevertheless, an ability to extract quantitative performance measures such as passage-time distributions from performance models of these systems is critical for providers of these services. Indeed, without such an ability, they remain unable to offer realistic end-to-end service level agreements (SLAs) which they can have any confidence of honouring. Additionally, this must be possible in a short enough period of time to allow many different parameter combinations in a complex system to be tested. If we can achieve this rapid performance analysis goal, it will enable service providers and engineers to determine the cost-optimal behaviour which satisfies the SLAs. In this thesis, we develop a scalable performance analysis framework for the grouped PEPA stochastic process algebra. Our approach is based on the approximation of key model quantities such as means and variances by tractable systems of ordinary differential equations (ODEs). Crucially, the size of these systems of ODEs is independent of the number of interacting entities within the model, making these analysis techniques extremely scalable. The reliability of our approach is directly supported by convergence results and, in some cases, explicit error bounds. We focus on extracting passage-time measures from performance models since these are very commonly the language in which a service level agreement is phrased. We design scalable analysis techniques which can handle passages defined both in terms of entire component populations as well as individual or tagged members of a large population. A precise and straightforward specification of a passage-time service level agreement is as important to the performance engineering process as its evaluation. This is especially true of large and complex models of industrial-scale systems. To address this, we introduce the unified stochastic probe framework. Unified stochastic probes are used to generate a model augmentation which exposes explicitly the SLA measure of interest to the analysis toolkit. In this thesis, we deploy these probes to define many detailed and derived performance measures that can be automatically and directly analysed using rapid ODE techniques. In this way, we tackle applicable problems at many levels of the performance engineering process: from specification and model representation to efficient and scalable analysis

Quantitative analysis of web services using SRMC

In this tutorial paper we present quantitative methods for analysing Web Services with the goal of understanding how they will perform under increased demand, or when asked to serve a larger pool of service subscribers. We use a process calculus called SRMC to model the service. We apply efficient analysis techniques to numerically evaluate our model. The process calculus and the numerical analysis are supported by a set of software tools which relieve the modeller of the burden of generating and evaluating a large family of related models. The methods are illustrated on a classical example of Web Service usage in a business-to-business scenario