Qing Zhang

George G. Yin

Using a singular perturbation approach, this is a systematic treatment of those systems that naturally arise in queuing theory, control and optimisation, and manufacturing, gathering a number of ideas which were previously scattered throughout the literature. The book presents results on asymptotic expansions of the corresponding probability distributions, functional occupation measures, exponential upper bounds, and asymptotic normality. To bridge the gap between theory and applications, a large portion of the book is devoted to various applications, thus reducing the dimensionality for problems under Markovian disturbances and providing tools for dealing with large-scale and complex real-world situations. Much of this stems from the authors'recent research, presenting results which have not appeared elsewhere. An important reference for researchers in applied mathematics, probability and stochastic processes, operations research, control theory, and optimisation.

A Singular Perturbation Approach

Continuous-Time Markov Chains and Applications

Jun Yang

Toshihisa Murofushi

Maoli Duan

Klaus Jahn

Lisheng Yu

Vestibular disorders in children

G. George Yin

This book focuses on two-time-scale Markov chains in discrete time. Our motivation stems from existing and emerging applications in optimization and control of complex systems in manufacturing, wireless communication, and ?nancial engineering. Much of our e?ort in this book is devoted to designing system models arising from various applications, analyzing them via analytic and probabilistic techniques, and developing feasible compu- tionalschemes. Ourmainconcernistoreducetheinherentsystemcompl- ity. Although each of the applications has its own distinct characteristics, all of them are closely related through the modeling of uncertainty due to jump or switching random processes. Oneofthesalientfeaturesofthisbookistheuseofmulti-timescalesin Markovprocessesandtheirapplications. Intuitively,notallpartsorcom- nents of a large-scale system evolve at the same rate. Some of them change rapidly and others vary slowly. The di?erent rates of variations allow us to reduce complexity via decomposition and aggregation. It would be ideal if we could divide a large system into its smallest irreducible subsystems completely separable from one another and treat each subsystem indep- dently. However, this is often infeasible in reality due to various physical constraints and other considerations. Thus, we have to deal with situations in which the systems are only nearly decomposable in the sense that there are weak links among the irreducible subsystems, which dictate the oc- sional regime changes of the system. An e?ective way to treat such near decomposability is time-scale separation. That is, we set up the systems as if there were two time scales, fast vs. slow. xii Preface Followingthetime-scaleseparation,weusesingularperturbationmeth- ology to treat the underlying systems.

Two-Time-Scale Methods and Applications

Discrete-Time Markov Chains

This book gives a systematic treatment of singularly perturbed systems that naturally arise in control and optimization, queueing networks, manufacturing systems, and financial engineering. It presents results on asymptotic expansions of solutions of Komogorov forward and backward equations, properties of functional occupation measures, exponential upper bounds, and functional limit results for Markov chains with weak and strong interactions. To bridge the gap between theory and applications, a large portion of the book is devoted to applications in controlled dynamic systems, production planning, and numerical methods for controlled Markovian systems with large-scale and complex structures in the real-world problems. This second edition has been updated throughout and includes two new chapters on asymptotic expansions of solutions for backward equations and hybrid LQG problems. The chapters on analytic and probabilistic properties of two-time-scale Markov chains have been almost completely rewritten and the notation has been streamlined and simplified. This book is written for applied mathematicians, engineers, operations researchers, and applied scientists. Selected material from the book can also be used for a one semester advanced graduate-level course in applied probability and stochastic processes.

A Two-Time-Scale Approach

Bo Shen

Yajuan Wang

Endong Wang

Guangyong Zhang

Xiaowei Lu

Qing Wu

The aim of this book is to explain to high-performance computing (HPC) developers how to utilize the Intel® Xeon PhiTM series products efficiently. To that end, it introduces some computing grammar, programming technology and optimization methods for using many-integrated-core (MIC) platforms and also offers tips and tricks for actual use, based on the authors’ first-hand optimization experience. The material is organized in three sections. The first section, “Basics of MIC”, introduces the fundamentals of MIC architecture and programming, including the specific Intel MIC programming environment. Next, the section on “Performance Optimization” explains general MIC optimization techniques, which are then illustrated step-by-step using the classical parallel programming example of matrix multiplication. Finally, “Project development” presents a set of practical and experience-driven methods for using parallel computing in application projects, including how to determine if a serial or parallel CPU program is suitable for MIC and how to transplant a program onto MIC. This book appeals to two main audiences: First, software developers for HPC applications – it will enable them to fully exploit the MIC architecture and thus achieve the extreme performance usually required in biological genetics, medical imaging, aerospace, meteorology and other areas of HPC. Second, students and researchers engaged in parallel and high-performance computing – it will guide them on how to push the limits of system performance for HPC applications.

How to Fully Exploit MIC Architectures

High-Performance Computing on the Intel® Xeon PhiTM

George Yin

Focusing on discrete-time-scale Markov chains, the contents of this book are an outgrowth of some of the authors' recent research. The motivation stems from existing and emerging applications in optimization and control of complex hybrid Markovian systems in manufacturing, wireless communication, and financial engineering. Much effort in this book is devoted to designing system models arising from these applications, analyzing them via analytic and probabilistic techniques, and developing feasible computational algorithms so as to reduce the inherent complexity. This book presents results including asymptotic expansions of probability vectors, structural properties of occupation measures, exponential bounds, aggregation and decomposition and associated limit processes, and interface of discrete-time and continuous-time systems. One of the salient features is that it contains a diverse range of applications on filtering, estimation, control, optimization, and Markov decision processes, and financial engineering. This book will be an important reference for researchers in the areas of applied probability, control theory, operations research, as well as for practitioners who use optimization techniques. Part of the book can also be used in a graduate course of applied probability, stochastic processes, and applications.

William M. McEneaney

In view of Professor Wendell Fleming's many fundamental contributions, his profound influence on the mathematical and systems theory communi ties, his service to the profession, and his dedication to mathematics, we have invited a number of leading experts in the fields of control, optimiza tion, and stochastic systems to contribute to this volume in his honor on the occasion of his 70th birthday. These papers focus on various aspects of stochastic analysis, control theory and optimization, and applications. They include authoritative expositions and surveys as well as research papers on recent and important issues. The papers are grouped according to the following four major themes: (1) large deviations, risk sensitive and Hoc control, (2) partial differential equations and viscosity solutions, (3) stochastic control, filtering and parameter esti mation, and (4) mathematical finance and other applications. We express our deep gratitude to all of the authors for their invaluable contributions, and to the referees for their careful and timely reviews. We thank Harold Kushner for having graciously agreed to undertake the task of writing the foreword. Particular thanks go to H. Thomas Banks for his help, advice and suggestions during the entire preparation process, as well as for the generous support of the Center for Research in Scientific Computation. The assistance from the Birkhauser professional staff is also greatly appreciated.

A Volume in Honor of Wendell H. Fleming

Stochastic Analysis, Control, Optimization and Applications

This book overviews the current status of research and development activities of CNTs in nanodevices, nanomaterials, or nanofabrication. This book presents 15 state-of-the-art review articles that cover CNT synthesis technologies for growing highly orientated CNTs, chirality-pure CNTs and CNTs at a large throughput and low cost, CNT assembly techniques, CNT sorting and separation processes, CNT functionalization engineering for more functionalities, CNT fundamental properties and their practical/potential electrical, electronic, optical, mechanical, chemical and biological applications.

Carbon Nanotubes and Their Applications

Recent Advances in Control and Optimization of Manufacturing Systems

Daniel Smith

Stephen Stanley

Riyaz Shariff

Audrey Cudrak

This study shows that advanced artificial neural network (ANN) model-based control systems can be used for drinking water treatment process control. ANN technology, an artificial intelligence technology that has the ability to learn patterns and relationships contained in sets of data, is the most powerful modeling tool currently available to the drinking water treatment industry. ANN predicts the output of a process given the values of process inputs and process control variables. The results of this project have the potential to revolutionize the way in which drinking water utilities optimize and control their unit processes to efficiently and consistently supply high quality drinking water

Real-time Artificial Intelligence Control and Optimization of a Full-scale WTP

Everyday, organizations release new services and generate data that we access on the Web in the form of digital goods. Digital goods are targeted by fraudsters who seek monetary gain as a result of malicious activities. These activities include stealing sensitive data, falsifying Web traffic, and spamming the Web, which can cost upwards of billions of dollars a year in lost revenue. This dissertation looks at three systems that validate or safeguard digital goods. First, I present Sifter, a system that assesses the quality of digital goods in the form of Web traffic. Sifter works via instrumentation of duplicate servers that receive traffic from separate sources. This instrumentation examines various metrics including mouse activity, click through rate, user-agent strings, timing metrics, and blacklists. Sifter compares these metrics across different traffic providers that vary in reputation. As a result, Sifter spots significant differences in the quality of traffic sources and sheds light on the savings offered by low-cost, bulk traffic digital goods. I then move from detecting fraudulent digital goods to Neon, which focuses on providing a framework that facilitates better data policy management on derived digital goods. Neon tracks every byte on a server by tinting them at the virtualization layer. As result, the flow of every byte in the system can be tracked without modification to guest operating systems or user applications. Neon then applies different management policies to tinted bytes, which can be used to control the flow of digital goods within an organization. Last, I consider the case where an organization must detect fraudulent digital goods outside of their network with DSpin. Specifically, DSpin detects spinning on the Web, where a spun article has words replaced and content restructured to possess similar meaning but different appearance. DSpin operates by identifying immutable words in the article that remain unchanged after spinning and comparing them between articles. I show that DSpin is an effective means of detecting spun digital goods. Each of these three systems detect and prevent fraudster attacks by examining source information. Indeed, I show that source information can be pivotal in safeguarding and validating digital goods.

Qing Zhang

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