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Written with computer scientists and engineers in mind, this book brings queueing theory decisively back to computer science.
This book constitutes the thoroughly refereed proceedings of the 5th International Workshop, PMBS 2014 in New Orleans, LA, USA in November 2014. The 12 full and 2 short papers presented in this volume were carefully reviewed and selected from 53 submissions. The papers cover topics on performance benchmarking and optimization; performance analysis and prediction; and power, energy and checkpointing.
As computers become more complex, the number and complexity of the tasks facing the computer architect have increased. Computer performance often depends in complex way on the design parameters and intuition that must be supplemented by performance studies to enhance design productivity. This book introduces computer architects to computer system performance models and shows how they are relatively simple, inexpensive to implement, and sufficiently accurate for most purposes. It discusses the development of performance models based on queuing theory and probability. The text also shows how they are used to provide quick approximate calculations to indicate basic performance tradeoffs and narrow the range of parameters to consider when determining system configurations. It illustrates how performance models can demonstrate how a memory system is to be configured, what the cache structure should be, and what incremental changes in cache size can have on the miss rate. A particularly deep knowledge of probability theory or any other mathematical field to understand the papers in this volume is not required.
Engineering mechanics is one of the fundamental branches of science that is important in the education of professional engineers of any major. Most of the basic engineering courses, such as mechanics of materials, fluid and gas mechanics, machine design, mechatronics, acoustics, vibrations, etc. are based on engineering mechanics courses. In order to absorb the materials of engineering mechanics, it is not enough to consume just theoretical laws and theorems—a student also must develop an ability to solve practical problems. Therefore, it is necessary to solve many problems independently. This book is a part of a four-book series designed to supplement the engineering mechanics courses. This series instructs and applies the principles required to solve practical engineering problems in the following branches of mechanics: statics, kinematics, dynamics, and advanced kinetics. Each book contains between 6 and 8 topics on its specific branch and each topic features 30 problems to be assigned as homework, tests, and/or midterm/final exams with the consent of the instructor. A solution of one similar sample problem from each topic is provided. This first book contains seven topics of statics, the branch of mechanics concerned with the analysis of forces acting on construction systems without an acceleration (a state of the static equilibrium). The book targets the undergraduate students of the sophomore/junior level majoring in science and engineering.
Poor performance is one of the main quality-related shortcomings that cause software projects to fail. Thus, the need to address performance concerns early during the software development process is fully acknowledged, and there is a growing interest in the research and software industry communities towards techniques, methods and tools that permit to manage system performance concerns as an integral part of software engineering. Model-based software performance analysis introduces performance concerns in the scope of software modeling, thus allowing the developer to carry on performance analysis throughout the software lifecycle. With this book, Cortellessa, Di Marco and Inverardi provide the cross-knowledge that allows developers to tackle software performance issues from the very early phases of software development. They explain the basic concepts of performance analysis and describe the most representative methodologies used to annotate and transform software models into performance models. To this end, they go all the way from performance primers through software and performance modeling notations to the latest transformation-based methodologies. As a result, their book is a self-contained reference text on software performance engineering, from which different target groups will benefit: professional software engineers and graduate students in software engineering will learn both basic concepts of performance modeling and new methodologies; while performance specialists will find out how to investigate software performance model building.
This textbook provides an introduction to common methods of performance modeling and analysis of communication systems. These methods form the basis of traffic engineering, teletraffic theory, and analytical system dimensioning. The fundamentals of probability theory, stochastic processes, Markov processes, and embedded Markov chains are presented. Basic queueing models are described with applications in communication networks. Advanced methods are presented that have been frequently used in recent practice, especially discrete-time analysis algorithms, or which go beyond classical performance measures such as Quality of Experience or energy efficiency. Recent examples of modern communication networks include Software Defined Networking and the Internet of Things. Throughout the book, illustrative examples are used to provide practical experience in performance modeling and analysis. Target group: The book is aimed at students and scientists in computer science and technical computer science, operations research, electrical engineering and economics.
The text is designed for engineering students at the senior undergraduate level and first-year students at graduate level, and professionals (R&D engineers in the industry and factory managers). The authors offer a unique effort in presenting a unified and systematic treatment of various modeling methodologies and analysis techniques for performance evaluation of automated manufacturing systems. The text begins with an overview of automated manufacturing systems, and then provides a clear and comprehensive discussion of three principal analytical modeling paradigms: Markov Chains, Queues and Queuing Networks, and Petri Nets. Salient Features • Present the first ever treatment of the mathematical modeling of manufacturing systems. • Offers a unified study of principal analytical modeling paradigms for automated manufacturing systems. • Discusses many recent research contributions in the area of modeling of automated manufacturing systems. • Discusses many recent research contributions in the area of modeling of automated manufacturing systems, including deadlock modeling, transient analysis, queuing network approximations, Petri Net modeling, and integrated analytical modeling. • Provides a large number of exercises and problems.
“If this book had been available to Healthcare.gov’s contractors, and they read and followed its life cycle performance processes, there would not have been the enormous problems apparent in that application. In my 40+ years of experience in building leading-edge products, poor performance is the single most frequent cause of the failure or cancellation of software-intensive projects. This book provides techniques and skills necessary to implement performance engineering at the beginning of a project and manage it throughout the product’s life cycle. I cannot recommend it highly enough.” –Don Shafer, CSDP, Technical Fellow, Athens Group, LLC Poor performance is a frequent cause of software project failure. Performance engineering can be extremely challenging. In Foundations of Software and System Performance Engineering, leading software performance expert Dr. André Bondi helps you create effective performance requirements up front, and then architect, develop, test, and deliver systems that meet them. Drawing on many years of experience at Siemens, AT&T Labs, Bell Laboratories, and two startups, Bondi offers practical guidance for every software stakeholder and development team participant. He shows you how to define and use metrics; plan for diverse workloads; evaluate scalability, capacity, and responsiveness; and test both individual components and entire systems. Throughout, Bondi helps you link performance engineering with everything else you do in the software life cycle, so you can achieve the right performance–now and in the future–at lower cost and with less pain. This guide will help you • Mitigate the business and engineering risk associated with poor system performance • Specify system performance requirements in business and engineering terms • Identify metrics for comparing performance requirements with actual performance • Verify the accuracy of measurements • Use simple mathematical models to make predictions, plan performance tests, and anticipate the impact of changes to the system or the load placed upon it • Avoid common performance and scalability mistakes • Clarify business and engineering needs to be satisfied by given levels of throughput and response time • Incorporate performance engineering into agile processes • Help stakeholders of a system make better performance-related decisions • Manage stakeholders’ expectations about system performance throughout the software life cycle, and deliver a software product with quality performance André B. Bondi is a senior staff engineer at Siemens Corp., Corporate Technologies in Princeton, New Jersey. His specialties include performance requirements, performance analysis, modeling, simulation, and testing. Bondi has applied his industrial and academic experience to the solution of performance issues in many problem domains. In addition to holding a doctorate in computer science and a master’s in statistics, he is a Certified Scrum Master.
This book demonstrates how to model the entire target acquisition process using either visible or infrared imaging systems. Beginning with an overview on electro-optical system design, the text introduces the complexity of various design considerations. A discussion of the differing types of visible and infrared sensors outlines basic wavelength issues and provides definitions of baseline hardware solutions.