Performance Engineering and Stochastic Modeling


Book Description

This book constitutes the refereed proceedings of the 17th European Workshop on Computer Performance Engineering, EPEW 2021, and the 26th International Conference, on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2021, held in December 2021. The conference was held virtually due to COVID 19 pandemic. The 29 papers presented in this volume were carefully reviewed and selected from 39 submissions. The papers presented at the workshop reflect the diversity of modern performance evaluation, with topics ranging from modeling and analysis of network/control protocols and high performance/big data information systems, analysis of scheduling, blockchain technology, analytical modeling and simulation of computer and network systems.




An Introduction to Stochastic Modeling


Book Description

An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.




Computer Performance Engineering and Stochastic Modelling


Book Description

This book constitutes the refereed proceedings of the 19th European Workshop on Computer Performance Engineering, EPEW 2023, and 27th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2023, held in Florence, Italy, in June 2023. The 26 papers presented in this volume were carefully reviewed and selected from 35 submissions. The papers presented at the workshop reflect the diversity of modern performance engineering. The sessions covered a wide range of topics including robustness analysis, machine learning, edge and cloud computing, as well as more traditional topics on stochastic modelling, techniques and tools.




Formal Methods and Stochastic Models for Performance Evaluation


Book Description

This book constitutes the refereed proceedings of the 4th European Performance Engineering Workshop, EPEW 2007, held in Berlin, Germany, September 27-28, 2007. The 20 revised full papers presented were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections on Markov Chains, Process Algebra, Wireless Networks, Queueing Theory and Applications of Queueing, Benchmarking and Bounding, Grid and Peer-to-Peer Systems.




Formal Methods and Stochastic Models for Performance Evaluation


Book Description

This book constitutes the refereed proceedings of the Third European Performance Engineering Workshop, EPEW 2006, held in Budapest, Hungary in June 2006. The 16 revised full papers presented were carefully reviewed and selected from 40 submissions. The papers are organized in topical sections on stochastic process algebra, workloads and benchmarks, theory of stochastic processes, formal dependability and performance evaluation, as well as queues, theory and practice.




Performance Analysis of Communication Systems


Book Description

Algorithm 396 A.4.6 General Execution Policies 398 A.5 Transient Analysis of DSPNs 401 A.5.1 Solution Algorithm for Periodic DSPNs 401 A.5.2 Solution Algorithm for Non-periodic DSPNs 403 List of Abbreviations 407 Glossary of Notation 411 References 419 Index 433.




Performance Modeling and Engineering


Book Description

With the fast development of networking and software technologies, information processing infrastructure and applications have been growing at an impressive rate in both size and complexity, to such a degree that the design and development of high performance and scalable data processing systems and networks have become an ever-challenging issue. As a result, the use of performance modeling and m- surementtechniquesas a critical step in designand developmenthas becomea c- mon practice. Research and developmenton methodologyand tools of performance modeling and performance engineering have gained further importance in order to improve the performance and scalability of these systems. Since the seminal work of A. K. Erlang almost a century ago on the mod- ing of telephone traf c, performance modeling and measurement have grown into a discipline and have been evolving both in their methodologies and in the areas in which they are applied. It is noteworthy that various mathematical techniques were brought into this eld, including in particular probability theory, stochastic processes, statistics, complex analysis, stochastic calculus, stochastic comparison, optimization, control theory, machine learning and information theory. The app- cation areas extended from telephone networks to Internet and Web applications, from computer systems to computer software, from manufacturing systems to s- ply chain, from call centers to workforce management.




Stochastic Models in Reliability Engineering


Book Description

This book is a collective work by many leading scientists, analysts, mathematicians, and engineers who have been working at the front end of reliability science and engineering. The book covers conventional and contemporary topics in reliability science, all of which have seen extended research activities in recent years. The methods presented in this book are real-world examples that demonstrate improvements in essential reliability and availability for industrial equipment such as medical magnetic resonance imaging, power systems, traction drives for a search and rescue helicopter, and air conditioning systems. The book presents real case studies of redundant multi-state air conditioning systems for chemical laboratories and covers assessments of reliability and fault tolerance and availability calculations. Conventional and contemporary topics in reliability engineering are discussed, including degradation, networks, and dynamic reliability, resilience, and multi-state systems, all of which are relatively new topics to the field. The book is aimed at engineers and scientists, as well as postgraduate students involved in reliability design, analysis, and experiments and applied probability and statistics.




Stochastic Models, Estimation, and Control


Book Description

This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.




Stochastic Simulation Optimization


Book Description

With the advance of new computing technology, simulation is becoming very popular for designing large, complex and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that are computationally intractable. Moreover, to obtain a sound statistical estimate at a specified level of confidence, a large number of simulation runs (or replications) is usually required for each design alternative. If the number of design alternatives is large, the total simulation cost can be very expensive. Stochastic Simulation Optimization addresses the pertinent efficiency issue via smart allocation of computing resource in the simulation experiments for optimization, and aims to provide academic researchers and industrial practitioners with a comprehensive coverage of OCBA approach for stochastic simulation optimization. Starting with an intuitive explanation of computing budget allocation and a discussion of its impact on optimization performance, a series of OCBA approaches developed for various problems are then presented, from the selection of the best design to optimization with multiple objectives. Finally, this book discusses the potential extension of OCBA notion to different applications such as data envelopment analysis, experiments of design and rare-event simulation.