Ulrich Herzog

Process algebra for performance evaluation

This paper surveys the theoretical developments in the field of stochastic process algebras, process algebras where action occurrences may be subject to a delay that is determined by a random variable. A huge class of resource-sharing systems - like large-scale computers, client-server architectures, networks - can accurately be described using such stochastic specification formalisms. The main emphasis of this paper is the treatment of operational semantics, notions of equivalence, and (sound and complete) axiomatisations of these equivalences for different types of Markovian process algebras, where delays are governed by exponential distributions. Starting from a simple actionless algebra for describing time-homogeneous continuous-time Markov chains, we consider the integration of actions and random delays both as a single entity (like in known Markovian process algebras like TIPP, PEPA and EMPA) and as separate entities (like in the timed process algebras timed CSP and TCCS). In total we consider four related calculi and investigate their relationship to existing Markovian process algebras. We also briefly indicate how one can profit from the separation of time and actions when incorporating more general, non-Markovian distributions.

Multiprocessor and Distributed System Design: The Integration of Functional Specification and Performance Analysis Using Stochastic Process Algebras

We introduce Stochastic Process Algebras as a novel approach for the structured design and analysis of both the functional behaviour and performance characteristics of parallel and distributed systems. This is achieved by integrating performance modelling and analysis into the powerful and well investigated formal description technique of process algebras.

Formal methods for performance evaluation

The main goal of this contribution is to advocate the increased use of formal methods (FM) in the field of performance evaluation (PE). Moreover, we try to reduce the mutual reservations between both areas, formal specification techniques and performance evaluation since both can profit from such an integration: FMs may find their way into a new and very attractive area of applications and some fundamental problems of PE may be overcome. The first part summarizes the evolution of PE, its methodology and the basic concepts of performance modeling and analysis, elaborated in specific contributions of this book. Classical modeling and analysis techniques have a high standard and have been quite successful. However, there are important problem classes still open, and there are some fundamental deficiencies: Task interdependencies and synchronization, interfacing in modeling hierarchies, methods and tools for automating the performance engineering process are typical examples. We therefore advocate the integration of FMs and PE and survey three advanced approaches, again, treated in detail in specific contributions: Stochastic Petri-Nets, Stochastic Activity Networks and Stochastic Process Algebras. We try to summarize our own experience with these techniques and conclude with a list of challenging topics and current research directions.

Compositional performance modelling with the TIPPtool

Stochastic process algebras have been proposed as compositional specification formalisms for performance models. In this paper, we describe a tool which aims at realising all beneficial aspects of compositional performance modelling, the TIPPtool. It incorporates methods for compositional specification as well as solution, based on state-of-the-art techniques, and wrapped in a user-friendly graphical front end. Apart from highlighting the general benefits of the tool, we also discuss some lessons learned during development and application of the TIPPtool. A non-trivial model of a real life communication system serves as a case study to illustrate benefits and limitations.

Stochastic process algebras—between LOTOS and Markov chains

Abstract This paper introduces stochastic process algebras as an approach for the structured design and analysis of both the functional behavior and performance characteristics of parallel and distributed systems. This is achieved by integrating stochastic modelling and analysis into process algebras like CCS or LOTOS. We demonstrate how notions of equivalent behavior – substantial for process algebras – stand in a new light for stochastic process algebras. In particular we discuss the impact of stochastic versions of such equivalences on compositional performance analysis by means of a running example. In addition we discuss analysis techniques, tool support and include a survey of related work as well as recent trends in this area.

Performance validation tools for software/hardware systems

Abstract It is common for software/hardware systems to be fully designed and functionally tested before an attempt is made to verify performance characteristics. Unsatisfactory performance, when discovered late in a system’s development, can cause a costly redesign and implementation of software or hardware and is likely to result in late system delivery. The goal of system performance validation is to provide assurance that a system as a whole is likely to meet its quantitative goals before the system is complete. It exploits performance engineering methods and tools to systematically construct and evaluate predictive system models. The tools must correctly predict system performance at some useful abstraction. This paper compares layered queueing models (LQMs) and stochastic process algebras (SPAs) and their support for system performance validation. In particular, we focus on abstraction and level detail within models and automated model building.

Stochastic process algebras: integrating qualitative and quantitative modelling

Stochastic process algebras (SPA) have emerged from work over the last five years investigating the use of process algebras for performance modelling. Like other stochastic extensions of existing system description techniques, they offer exciting possibilities for integrating qualitative and quantitative analysis. The use of such languages facilitates the early consideration of the temporal properties of an emerging design Unlike existing approaches, SPA exploit the compositionality, known from classical process algebras. The algebraic framework of this compositionality has advantages for both model construction and model solution.

Exploiting stochastic process algebra achievements for generalized stochastic Petri nets

Constructing large generalized stochastic Petri nets (GSPN) by hierarchical composition of smaller components is a promising way to cope with the complexity of the design process for models of real hardware and software systems. The composition of nets is inspired by process algebraic operators. A solid theoretical framework of such operators relies on equivalences that are substitutive with respect to the operators. Practically important, such equivalences allow compositional reduction techniques, where components may be replaced by smaller but equivalent nets without affecting significant properties of the whole model. However substitutive equivalence notions for GSPN have not been published. In this paper we adopt operators and equivalences originally developed in the context of stochastic process algebras to GSPN. The equivalences are indeed substitutive with respect to two composition operators, parallel composition and hiding. This bears the potential to exploit hierarchies in the model definition to obtain performance indices of truly large composite GSPN by stepwise compositional reduction. We illustrate the effect of composition as well as compositional reduction by means of a running example. A case study of a workstation cluster highlights the potential of compositional reduction.

Stochastic Process Algebras

We introduce Stochastic Process Algebras as a novel approach for the structured design and analysis of both the functional behaviour and performability (i.e performance and dependability) characteristics of parallel and distributed systems. This is achieved by integrating stochastic modelling and analysis into the powerful and well investigated formal description techniques of process algebras.

Compositional Performance Modelling with TIPPtool

Stochastic Process Algebras have been proposed as compositional specification formalisms for performance models. In this paper, we describe a tool which aims at realising all beneficial aspects of compositional performance modelling, the TIPPtool. It incorporates methods for compositional specification as well as solution, based on state-of-the-art-techniques, and wrapped in a user-friendly graphical front end.