An overview of queueing network modelling. Conducting a modelling study. Fundamental laws. General analytic technique. Bounds on performance. Models with one job class. Models with multiple job classes. Flow equivalence and hierarchical modelling. Representing specific subsystems. Memory. Disk I/O. Processors. Parameterization. Existing systems. Evolving systems. Proposed systems. Perspective. Using queueing network modelling software. Appendices. Constructing a model from RMF data. An implementation of single class, exact MVA. An implementation of multiple class, exact MVA. Load dependent service centers. Index.

Praise from the Reviewers: "The practicality of the subject in a real-world situation distinguishes this book from others available on the market." —Professor Behrouz Far, University of Calgary "This book could replace the computer organization texts now in use that every CS and CpE student must take. . . . It is much needed, well written, and thoughtful." —Professor Larry Bernstein, Stevens Institute of Technology A distinctive, educational text onsoftware performance and scalability This is the first book to take a quantitative approach to the subject of software performance and scalability. It brings together three unique perspectives to demonstrate how your products can be optimized and tuned for the best possible performance and scalability: The Basics—introduces the computer hardware and software architectures that predetermine the performance and scalability of a software product as well as the principles of measuring the performance and scalability of a software product Queuing Theory—helps you learn the performance laws and queuing models for interpreting the underlying physics behind software performance and scalability, supplemented with ready-to-apply techniques for improving the performance and scalability of a software system API Profiling—shows you how to design more efficient algorithms and achieve optimized performance and scalability, aided by adopting an API profiling framework (perfBasic) built on the concept of a performance map for drilling down performance root causes at the API level Software Performance and Scalability gives you a specialized skill set that will enable you to design and build performance into your products with immediate, measurable improvements. Complemented with real-world case studies, it is an indispensable resource for software developers, quality and performance assurance engineers, architects, and managers. It is anideal text for university courses related to computer and software performance evaluation and can also be used to supplement a course in computer organization or in queuing theory for upper-division and graduate computer science students.

The author is one of the prominent researchers in the field of Data Envelopment Analysis (DEA), a powerful data analysis tool that can be used in performance evaluation and benchmarking. This book is based upon the author’s years of research and teaching experiences. It is difficult to evaluate an organization’s performance when multiple performance metrics are present. The difficulties are further enhanced when the relationships among the performance metrics are complex and involve unknown tradeoffs. This book introduces Data Envelopment Analysis (DEA) as a multiple-measure performance evaluation and benchmarking tool. The focus of performance evaluation and benchmarking is shifted from characterizing performance in terms of single measures to evaluating performance as a multidimensional systems perspective. Conventional and new DEA approaches are presented and discussed using Excel spreadsheets — one of the most effective ways to analyze and evaluate decision alternatives. The user can easily develop and customize new DEA models based upon these spreadsheets. DEA models and approaches are presented to deal with performance evaluation problems in a variety of contexts. For example, a context-dependent DEA measures the relative attractiveness of similar operations/processes/products. Sensitivity analysis techniques can be easily applied, and used to identify critical performance measures. Two-stage network efficiency models can be utilized to study performance of supply chain. DEA benchmarking models extend DEA’s ability in performance evaluation. Various cross efficiency approaches are presented to provide peer evaluation scores. This book also provides an easy-to-use DEA software — DEAFrontier. This DEAFrontier is an Add-In for Microsoft® Excel and provides a custom menu of DEA approaches. This version of DEAFrontier is for use with Excel 97-2013 under Windows and can solve up to 50 DMUs, subject to the capacity of Excel Solver. It is an extremely powerful tool that can assist decision-makers in benchmarking and analyzing complex operational performance issues in manufacturing organizations as well as evaluating processes in banking, retail, franchising, health care, public services and many other industries.

This book constitutes the proceedings of the 11th International Conference on Quantitative Evaluation of Systems, QEST 2014, held in Florence, Italy, in September 2014. The 24 full papers and 5 short papers included in this volume were carefully reviewed and selected from 61 submissions. They are organized in topical sections named: Kronecker and product form methods; hybrid systems; mean field/population analysis; models and tools; simulation; queueing, debugging and tools; process algebra and equivalences; automata and Markov process theory; applications, theory and tools; and probabilistic model checking.

This book constitutes the proceedings of the 15th International Conference on Quantitative Evaluation Systems, QEST 2018, held in Beijing, China, in September 2018. The 24 full papers presented were carefully reviewed and selected from 51 submissions. The papers cover topics in the field of quantitative evaluation and verification of computer systems and networks through stochastic models and measurements emphasizing two frontier topics in research: quantitative information flow for security and industrial formal methods.

This book constitutes the proceedings of the 12th International Conference on Quantitative Evaluation of Systems, QEST 2015, held in Madrid, Spain, in September 2015. 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-paper invited talk.

This book constitutes the proceedings of the 18th International Conference on Quantitative Evaluation Systems, QEST 2021, held in Paris, France, in August 2021. The 21 full papers and 2 short papers presented together with 2 keynote papers were carefully reviewed and selected from 47 submissions. The papers are organized in the following topics: probabilistic model checking; quantitative models and metamodels: analysis and validation; queueing systems; learning and verification; simulation; performance evaluation; abstractions and aggregations; and stochastic models.

This book constitutes the proceedings of the 20th International Conference on Quantitative Evaluation of Systems, QEST 2023, which took place in Antwerp, Belgium, in September 2023. The 23 papers included in this book were carefully reviewed and selected from 44 submissions. They deal with current topics in quantitative evaluation and verification of computer systems and networks, focusing on data-driven and machine-learning systems, case studies, and tool papers. The book also contains the extended abstract of the invited talk from David Parker.

This book shares key insights into system performance and management analytics, demonstrating how the field of analytics is currently changing and how it is used to monitor companies’ efforts to drive performance.Managing business performance facilitates the effective accomplishment of strategic and operational goals, and there is a clear and direct correlation between using performance management applications and improved business and organizational results. As such, performance and management analytics can yield a range of direct and indirect benefits, boost operational efficiency and unlock employees’ latent potential, while at the same time aligning services with overarching goals.The book addresses a range of topics, including software reliability assessment, testing, quality management, system-performance management, analysis using soft-computing techniques, and management analytics. It presents a balanced, holistic approach to viewing the world from both a technical and managerial perspective by considering performance and management analytics. Accordingly, it offers a comprehensive guide to one of the most pressing issues in today’s technology-dominated world, namely, that most companies and organizations find themselves awash in a sea of data, but lack the human capital, appropriate tools and knowledge to use it to help them create a competitive edge.

This book describes and evaluates existing models of human performance and their use in the design and evaluation of new human-technology systems. Its primary focus is on the modeling of system operators who perform supervisory and manual control tasks. After an introduction on human performance modeling, the book describes information processing, control theory, task network, and knowledge-based models. It explains models of human performance in aircraft operations, nuclear power plant control, maintenance, and the supervisory control of process control systems, such as oil refineries. The book concludes with a discussion of model parameterization and validation and recommends a number of lines of research needed to strengthen model development and application.