Analysis and Synthesis of Computer Systems presents a broad overview of methods that are used to evaluate the performance of computer systems and networks, manufacturing systems, and interconnected services systems. Aside from a highly readable style that rigorously addresses all subjects, this second edition includes new chapters on numerical methods for queueing models and on G-networks, the latter being a new area of queuing theory that one of the authors has pioneered.This book will have a broad appeal to students, practitioners and researchers in several different areas, including practicing computer engineers as well as computer science and engineering students./a
Based on the author's experience in industry, this book focuses on simple techniques for solving everyday problems in systems design and analysis. All techniques are covered in a non-mathematical way, so that no statistics expertise is necessary.
This Handbook is a collection of chapters on key issues in the design and analysis of computer simulation experiments on models of stochastic systems. The chapters are tightly focused and written by experts in each area. For the purpose of this volume "simulation refers to the analysis of stochastic processes through the generation of sample paths (realization) of the processes. Attention focuses on design and analysis issues and the goal of this volume is to survey the concepts, principles, tools and techniques that underlie the theory and practice of stochastic simulation design and analysis. Emphasis is placed on the ideas and methods that are likely to remain an intrinsic part of the foundation of the field for the foreseeable future. The chapters provide up-to-date references for both the simulation researcher and the advanced simulation user, but they do not constitute an introductory level 'how to' guide. Computer scientists, financial analysts, industrial engineers, management scientists, operations researchers and many other professionals use stochastic simulation to design, understand and improve communications, financial, manufacturing, logistics, and service systems. A theme that runs throughout these diverse applications is the need to evaluate system performance in the face of uncertainty, including uncertainty in user load, interest rates, demand for product, availability of goods, cost of transportation and equipment failures.* Tightly focused chapters written by experts* Surveys concepts, principles, tools, and techniques that underlie the theory and practice of stochastic simulation design and analysis* Provides an up-to-date reference for both simulation researchers and advanced simulation users
Simulation and molding are efficient techniques that can aid the city and regional planners and engineers in optimizing the operation of urban systems such as traffic light control, highway toll automation, consensus building, public safety, and environmental protection. When modeling transportation systems such as freeway systems, arterial or downtown grid systems, the city planner and engineer is concerned with capturing the varied interactions between drivers, automobiles, and the infrastructure. Modeling and simulation are used to effectively optimize the design and operation of all of these urban systems. It is possible that in an urban simulation community workshop, citizens can work interactively in front of computers and be able using the click of the mouse to walk up to their own front porch, looking at the proposed shopping mall alternatives across the street from virtually any angle and proposed bridge or tunnel and see how it can reduce traffic congestion. Buildings can be scaled down or taken out, their orientation can be changed in order to check the view and orientation in order to have better site with efficient energy-conservation. The stone or brick material on a building can be replaced by colored concrete, or more trees and lampposts can be placed on the site. Such flexibility in simulation and animation allows creative ideas in the design and orientation of urban sites to be demonstrated to citizens and decision makers before final realization.
Traditionally, models and methods for the analysis of the functional correctness of reactive systems, and those for the analysis of their performance (and - pendability) aspects, have been studied by di?erent research communities. This has resulted in the development of successful, but distinct and largely unrelated modeling and analysis techniques for both domains. In many modern systems, however, the di?erence between their functional features and their performance properties has become blurred, as relevant functionalities become inextricably linked to performance aspects, e.g. isochronous data transfer for live video tra- mission. During the last decade, this trend has motivated an increased interest in c- bining insights and results from the ?eld of formal methods – traditionally - cused on functionality – with techniques for performance modeling and analysis. Prominent examples of this cross-fertilization are extensions of process algebra and Petri nets that allow for the automatic generation of performance models, the use of formal proof techniques to assess the correctness of randomized - gorithms, and extensions of model checking techniques to analyze performance requirements automatically. We believe that these developments markthe - ginning of a new paradigm for the modeling and analysis of systems in which qualitative and quantitative aspects are studied from an integrated perspective. We are convinced that the further worktowards the realization of this goal will be a growing source of inspiration and progress for both communities.
This text provides an up-to-date treatment of the fundamental techniques and algorithms for numerical analysis of deterministic and stochastic Petri nets, a particular stochastic modelling formalism, and the application of this modelling formalism to performance analysis for parallel computer architectures.
Recent years have witnessed tremendous growth in the population of mobile users demanding high performance, reliability and quality-of-service (QoS). Wireless networks are undergoing rapid developments and dramatic changes in the underlying technologies, in order to cope with the difficulties posed by the scarce wireless resource as well as keep up with the increasing day-to-day demand for cost-effective service of multimedia applications. Predicting and optimising the performance and QoS of wireless networks using analytical modelling, simulation experiments, monitoring and testbed-based measurements are crucial to the proper design, tuning, resource management and capacity planning of such networks. This book is dedicated to review important developments and results, explore recent state-of-the-art research and discuss new strategies for performance modelling, analysis and enhancement of wireless networks. The objective is to make analytical modelling, simulation and measurement tools, and innovative performance evaluation methodology possible and understandable to a wider audience.
