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2 edition of Analysing performance of open queueing systems with stochastic process algebras found in the catalog.

Analysing performance of open queueing systems with stochastic process algebras

Amani Helmi El-Rayes

Analysing performance of open queueing systems with stochastic process algebras

by Amani Helmi El-Rayes

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  • 37 Currently reading

Published by University of Birmingham in Birmingham .
Written in English


Edition Notes

Thesis (Ph.D) - University of Birmingham, School of Computer Science, Faculty of Science.

Statementby Amani Helmi El-Rayes.
ID Numbers
Open LibraryOL18928300M

This book considers stochastic (queueing-based) models and is intended as a course text for computer science courses at the advanced undergraduate and Masters degree levels, as a reference for researchers in the field and as a handbook for professionals in the business of performance evaluation and design of computer architectures. Queueing theory is the mathematical study of waiting lines, or queues. A queueing model is constructed so that queue lengths and waiting time can be predicted. Queueing theory is generally considered a branch of operations research because the results are often used when making business decisions about the resources needed to provide a service.. Queueing theory has its origins in research by.

Introduction Specification of Queueing Models Stochastic Models for Arrival and Service Processes Structural Parameters Operating Policies The A/B/m /K Notation Open and Closed Queueing Systems Performance of a Queuing System Queueing System Dynamics Little's Law Analysis of Simple Markovian. Stochastic Processes and Models in Operations Research emphasizes mathematical tools and equations relevant for solving complex problems within business and industrial settings. This research-based publication aims to assist scholars, researchers, operations managers, and graduate-level students by providing comprehensive exposure to the.

In the second half of the book, the reader is introduced to stochastic processes. Subjects covered include renewal processes, queueing theory, Markov processes, matrix geometric techniques, reversibility, and networks of queues. Examples and applications are drawn from problems in computer performance s: 5.   Fig. 1 shows the connection loss probability P loss of the system with respect to the attack traffic load with different settings for the maximum allowable number of half-open connections N and holding time b for pending connections. Let λ 1 = 10/s as the parameter for the Poisson arrival process of the regular request packets. Let λ 2 = kλ 1, and clearly, the parameter k may be .


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Analysing performance of open queueing systems with stochastic process algebras by Amani Helmi El-Rayes Download PDF EPUB FB2

The 21 full papers presented in this book were carefully reviewed and selected from 30 submissions. The papers discuss the latest developments in analytical, numerical and simulation algorithms for stochastic systems, including Markov processes, queueing networks, stochastic Petri nets, process algebras, game theory, etc.

PEPA 1 ph is suitable for describing and analysing the performance of open queueing systems such as Ph=Ph=c and M=Ph=1 with duration of activities given by phase-type distributions.

Abstract. We introduce a Stochastic Process Algebra called PEPA 1 ph, based on Hillston's Performance Evaluation Process Algebra (PEPA). PEPA 1 ph is suitable for describing and analysing the performance of open queueing systems such as Ph=Ph=c and M=Ph=1 with duration of activities given by phase-type distributions.

In this tutorial we give an introduction to stochastic process algebras and their use in performance modelling, with a focus on the PEPA formalism. A brief introduction is given to the motivations for extending classical process algebra with stochastic times and probabilistic by: The book has a broad coverage of methods to calculate important probabilities, and gives attention to proving the general theorems.

It includes many recent topics, such as server-vacation models, diffusion approximations and optimal operating policies, and more about bulk-arrival and bull-service models than other general texts. Performance Evaluation Process Algebra (PEPA) [1] is an algebraic language which can be used to build models of computer systems which capture information about the performance of the system.

The analysis of a queueing system with fixed (deterministic) interarrival and service times does not present much difficulty.

We shall be concerned with models or systems where one or both (interarrival and service times) are stochastic. Their analyses will involve a stochastic description of the system and related performance measures, as discussed below. Further, we demonstrate that by creating a stochastic transition system, we can solve G/G/1/2 queues and, more generally, Markovian Process Algebras without the use of Markov Chains.

We present a process algebra for the performance modeling and evaluation of concurrent systems whose activity durations are expressed through general probability distributions. We first determine the class of generalized semi-Markov processes (GSMPs) as being the class of stochastic processes on which we must rely for performance evaluation to.

Performance analysis of queueing networks is one of the most challenging areas of queueing theory. The di culty stems from the presence of network feedback, which introduces a complicated multidimensional structure into the stochastic processes underlying the key performance measures.

Short of specialized. The 19 papers presented were carefully reviewed and selected from 42 submissions. They are organized in topical sections named: modelling and applications; tools; petri nets, process algebra and fault trees; applications; and queuing systems and hybrid systems.

The book also contains one full. N. Götz, U. Herzog, M. Rettelbach, “Multiprocessor and Distributed System Design: the Integration of Functional Specification and Performance Analysis Using Stochastic Process Algebras”, in Proc. of PERFORMANCE '93, Rome (Italy). Sample-Path Analysis of Queueing Systems uses a deterministic (sample-path) approach to analyze stochastic systems, primarily queueing systems and more general input-output systems.

Among other topics of interest it deals with establishing fundamental relations between asymptotic frequencies and averages, pathwise stability, and insensitivity.

Author by: J.A. White Languange: en Publisher by: Elsevier Format Available: PDF, ePub, Mobi Total Read: 17 Total Download: 99 File Size: 47,8 Mb Description: Analysis and Queueing Systems is a nine-chapter introductory text that considers the applied problem of analyzing queueing book outlines a sequence of steps, which if properly executed yield an improved design of the.

Stochastic process algebras, which combine the features of a process calculus with stochastic analysis, were introduced to enable compositional performance analysis of systems.

His research interests include stochastic models, stochastic processes, stochastic process algebra, manufacturing systems, communication networks, and network security. He has published over 30 papers in international research journals such as, Advances in Applied Probability, Queueing Systems and Stochastic Models.

Introduction to Discrete Event Systems Second Edition by Christos G. Cassandras Boston University Stéphane Lafortune The University of Michigan. Introduction Specification of Queueing Models Stochastic Models for Arrival and Service Processes Structural Parameters Operating Policies The A/B/m /K Notation Open and Closed Queueing Systems Performance of a Queuing System Queueing System Dynamics Little’s Law Analysis of Simple.

By integrating the necessary background on stochastic processes with the analysis of models, the work provides a sound foundational introduction to the modeling and analysis of queueing systems for a broad interdisciplinary audience of students in mathematics, statistics, and applied disciplines such as computer science, operations research.

Performance Evaluation Process Algebra (PEPA) is a high-level modelling language for distributed systems. In this paper we describe a novel approach to composing PEPA models where the language is supplemented with the structuring features and language constructs of a strongly typed higher-order functional programming language, Standard ML.

It employs a large number of examples to teach the students to use stochastic models of real-life systems to predict their performance, and use this analysis to design better systems. The book is devoted to the study of important classes of stochastic processes: discrete and continuous time Markov processes, Poisson processes, renewal and.Performance analysis and optimization of a pseudo-fault Geo/Geo/1 repairable queueing system with N-policy, setup time and multiple working vacations.

Journal of Industrial & Management Optimization,13 (3): doi: /jimo [9] Shaojun Lan, Yinghui Tang.1. Introduction 2.

Background 3. Performance evaluation process algebra 4. Modelling study: multi-server multi-queue systems 5. Notions of equivalence 6. Isomorphism and weak isomorphism 7. Strong .