Networking and Parallel/Distributed Computing 2012

Numerical algorithms, modern programming techniques, and parallel computing are often taught serially across different courses and different textbooks. The need to integrate concepts and tools usually comes only in employment or in research - after the courses are concluded - forcing the student to synthesise what is perceived to be three independent subfields into one. This book provides a seamless approach to stimulate the student simultaneously through the eyes of multiple disciplines, leading to enhanced understanding of scientific computing as a whole. The book includes both basic as well as advanced topics and places equal emphasis on the discretization of partial differential equations and on solvers. Some of the advanced topics include wavelets, high-order methods, non-symmetric systems, and parallelization of sparse systems. The material covered is suited to students from engineering, computer science, physics and mathematics.

The constantly increasing demand for more computing power can seem impossible to keep up with. However, multicore processors capable of performing computations in parallel allow computers to tackle ever larger problems in a wide variety of applications. This book provides a comprehensive introduction to parallel computing, discussing theoretical issues such as the fundamentals of concurrent processes, models of parallel and distributed computing, and metrics for evaluating and comparing parallel algorithms, as well as practical issues, including methods of designing and implementing shared- and distributed-memory programs, and standards for parallel program implementation, in particular MPI and OpenMP interfaces. Each chapter presents the basics in one place followed by advanced topics, allowing novices and experienced practitioners to quickly find what they need. A glossary and more than 80 exercises with selected solutions aid comprehension. The book is recommended as a text for adva

In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of parallelism. The authors begin by giving the reader a deeper understanding of the issues through a general examination of timing, data dependencies, and communication. These ideas are implemented with respect to shared memory, parallel and vector processing, and distributed memory cluster computing. Threads, OpenMP, and MPI are covered, along with code examples in Fortran, C, and Java. The principles of parallel computation are applied throughout as the authors cover traditional topics in a first course in scientific computing. Building on the fundamentals of floating point representation and numerical error, a thorough treatment of numerical linear algebra and eigenvector/eigenvalue problems is provided. By studying how these algorithms parallelize, the reader is able to explore parallelism inherent in other computations, such as Monte Carlo

In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of parallelism. The authors begin by giving the reader a deeper understanding of the issues through a general examination of timing, data dependencies, and communication. These ideas are implemented with respect to shared memory, parallel and vector processing, and distributed memory cluster computing. Threads, OpenMP, and MPI are covered, along with code examples in Fortran, C, and Java. The principles of parallel computation are applied throughout as the authors cover traditional topics in a first course in scientific computing. Building on the fundamentals of floating point representation and numerical error, a thorough treatment of numerical linear algebra and eigenvector/eigenvalue problems is provided. By studying how these algorithms parallelize, the reader is able to explore parallelism inherent in other computations, such as Monte Carlo

Discover the very latest game-theoretic approaches for designing, modeling, and optimizing emerging wireless communication networks and systems with this unique text. Providing a unified and comprehensive treatment throughout, it explains basic concepts and theories for designing novel distributed wireless networking mechanisms, describes emerging game-theoretic tools from an engineering perspective, and provides an extensive overview of recent applications. A wealth of new tools is covered - including matching theory and games with bounded rationality - and tutorial chapters show how to use these tools to solve current and future wireless networking problems in areas such as 5G networks, network virtualization, software defined networks, cloud computing, the Internet of Things, context-aware networks, green communications, and security. This is an ideal resource for telecommunications engineers, and researchers in industry and academia who are working on the design of efficient, scala

The arrival and popularity of multi-core processors has sparked a renewed interest in the development of parallel programs. Similarly, the availability of low-cost microprocessors and sensors has generated a great interest in embedded real-time programs. This book provides students and programmers whose backgrounds are in traditional sequential programming with the opportunity to expand their capabilities into parallel, embedded, real-time and distributed computing. It also addresses the theoretical foundation of real-time scheduling analysis, focusing on theory that is useful for actual applications. Written by award-winning educators at a level suitable for undergraduates and beginning graduate students, this book is the first truly entry-level textbook in the subject. Complete examples allow readers to understand the context in which a new concept is used, and enable them to build and run the examples, make changes, and observe the results.

This book sets out the principles of parallel computing in a way which will be useful to student and potential user alike. It includes coverage of both conventional and neural computers. The content of the book is arranged hierarchically. It explains why, where and how parallel computing is used; the fundamental paradigms employed in the field; how systems are programmed or trained; technical aspects including connectivity and processing element complexity; and how system performance is estimated (and why doing so is difficult). The penultimate chapter of the book comprises a set of case studies of archetypal parallel computers, each study written by an individual closely connected with the system in question. The final chapter correlates the various aspects of parallel computing into a taxonomy of systems.

This book sets out the principles of parallel computing in a way which will be useful to student and potential user alike. It includes coverage of both conventional and neural computers. The content of the book is arranged hierarchically. It explains why, where and how parallel computing is used; the fundamental paradigms employed in the field; how systems are programmed or trained; technical aspects including connectivity and processing element complexity; and how system performance is estimated (and why doing so is difficult). The penultimate chapter of the book comprises a set of case studies of archetypal parallel computers, each study written by an individual closely connected with the system in question. The final chapter correlates the various aspects of parallel computing into a taxonomy of systems.

In this 1991 book, Hilbers discusses the general case of how to use processors simultaneously in order to solve a single problem rather than any specific application, and develops a theory independent of particular architectures. He starts by introducing distributed computing with graph theory, and considers processor networks and their price/performance ratios. He goes on to look at obtaining homogeneous distributions of work over networks and considers examples. Finally he discusses message routing within a processor network. This is intended to be a fundamental treatment of the relevant subjects and is aimed at computer scientists and graduate students in computer science who have experience with parallel processing: it will also be useful to others interested in processor networks.

In this 1991 book, Hilbers discusses the general case of how to use processors simultaneously in order to solve a single problem rather than any specific application, and develops a theory independent of particular architectures. He starts by introducing distributed computing with graph theory, and considers processor networks and their price/performance ratios. He goes on to look at obtaining homogeneous distributions of work over networks and considers examples. Finally he discusses message routing within a processor network. This is intended to be a fundamental treatment of the relevant subjects and is aimed at computer scientists and graduate students in computer science who have experience with parallel processing: it will also be useful to others interested in processor networks.

This comprehensive treatment of network information theory and its applications provides the first unified coverage of both classical and recent results. With an approach that balances the introduction of new models and new coding techniques, readers are guided through Shannon's point-to-point information theory, single-hop networks, multihop networks, and extensions to distributed computing, secrecy, wireless communication, and networking. Elementary mathematical tools and techniques are used throughout, requiring only basic knowledge of probability, whilst unified proofs of coding theorems are based on a few simple lemmas, making the text accessible to newcomers. Key topics covered include successive cancellation and superposition coding, MIMO wireless communication, network coding, and cooperative relaying. Also covered are feedback and interactive communication, capacity approximations and scaling laws, and asynchronous and random access channels. This book is ideal for use in the

This comprehensive treatment of network information theory and its applications provides the first unified coverage of both classical and recent results. With an approach that balances the introduction of new models and new coding techniques, readers are guided through Shannon's point-to-point information theory, single-hop networks, multihop networks, and extensions to distributed computing, secrecy, wireless communication, and networking. Elementary mathematical tools and techniques are used throughout, requiring only basic knowledge of probability, whilst unified proofs of coding theorems are based on a few simple lemmas, making the text accessible to newcomers. Key topics covered include successive cancellation and superposition coding, MIMO wireless communication, network coding, and cooperative relaying. Also covered are feedback and interactive communication, capacity approximations and scaling laws, and asynchronous and random access channels. This book is ideal for use in the

This book presents the proceedings of the Distributed Ada '89 Symposium held at the University of Southampton in December. The objective of the symposium was to provide a platform for developers and users with experience in the areas of distributed and parallel environments to reveal the advantages and difficulties encountered. The impact of Ada-9X and other enhancements to the language were also explored.

From its earliest days, the Fortran programming language has been designed with computing efficiency in mind. The latest standard, Fortran 2008, incorporates a host of modern features, including object-orientation, array operations, user-defined types, and provisions for parallel computing. This tutorial guide shows Fortran programmers how to apply these features in twenty-first-century style: modular, concise, object-oriented, and resource-efficient, using multiple processors. It offers practical real-world examples of interfacing to C, memory management, graphics and GUIs, and parallel computing using MPI, OpenMP, and coarrays. The author also analyzes several numerical algorithms and their implementations and illustrates the use of several open source libraries. Full source code for the examples is available on the book's website.

From its earliest days, the Fortran programming language has been designed with computing efficiency in mind. The latest standard, Fortran 2008, incorporates a host of modern features, including object-orientation, array operations, user-defined types, and provisions for parallel computing. This tutorial guide shows Fortran programmers how to apply these features in twenty-first-century style: modular, concise, object-oriented, and resource-efficient, using multiple processors. It offers practical real-world examples of interfacing to C, memory management, graphics and GUIs, and parallel computing using MPI, OpenMP, and coarrays. The author also analyzes several numerical algorithms and their implementations and illustrates the use of several open source libraries. Full source code for the examples is available on the book's website.

This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements. Making task-appropriate algorithm and platform choices for large-scale machine learning requires understanding the benefits, trade-offs and constraints of the available options. Solutions presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters, concurrent programming frameworks including CUDA, MPI, MapReduce and DryadLINQ, and learning settings (supervised, unsupervised, semi-supervised and online learning). Extensive coverage of parallelization of boosted trees, SVMs, spectral clustering, belief propagation and other popular learning algo

This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements. Making task-appropriate algorithm and platform choices for large-scale machine learning requires understanding the benefits, trade-offs and constraints of the available options. Solutions presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters, concurrent programming frameworks including CUDA, MPI, MapReduce and DryadLINQ, and learning settings (supervised, unsupervised, semi-supervised and online learning). Extensive coverage of parallelization of boosted trees, SVMs, spectral clustering, belief propagation and other popular learning algo

JavaTech is a practical introduction to the Java programming language with an emphasis on the features that benefit technical computing. After presenting the basics of object-oriented programming in Java, it examines introductory topics such as graphical interfaces and thread processes. It goes on to review network programming and develops Web client-server examples for tasks such as monitoring remote devices. The focus then shifts to distributed computing with RMI. Finally, it examines how Java programs can access the local platform and interact with hardware. Topics include combining native code with Java, communication via serial lines, and programming embedded processors. An extensive web site supports the book with additional instructional materials. JavaTech demonstrates the ease with which Java can be used to create powerful network applications and distributed computing applications. It will be used as a textbook for programming courses, and by researchers who need to learn Jav

JavaTech is a practical introduction to the Java programming language with an emphasis on the features that benefit technical computing. After presenting the basics of object-oriented programming in Java, it examines introductory topics such as graphical interfaces and thread processes. It goes on to review network programming and develops Web client-server examples for tasks such as monitoring remote devices. The focus then shifts to distributed computing with RMI. Finally, it examines how Java programs can access the local platform and interact with hardware. Topics include combining native code with Java, communication via serial lines, and programming embedded processors. An extensive web site supports the book with additional instructional materials. JavaTech demonstrates the ease with which Java can be used to create powerful network applications and distributed computing applications. It will be used as a textbook for programming courses, and by researchers who need to learn Jav

Designing distributed computing systems is a complex process requiring a solid understanding of the design problems and the theoretical and practical aspects of their solutions. This comprehensive textbook covers the fundamental principles and models underlying the theory, algorithms and systems aspects of distributed computing. Broad and detailed coverage of the theory is balanced with practical systems-related issues such as mutual exclusion, deadlock detection, authentication, and failure recovery. Algorithms are carefully selected, lucidly presented, and described without complex proofs. Simple explanations and illustrations are used to elucidate the algorithms. Important emerging topics such as peer-to-peer networks and network security are also considered. With vital algorithms, numerous illustrations, examples and homework problems, this textbook is suitable for advanced undergraduate and graduate students of electrical and computer engineering and computer science. Practitioner

Stream processing is a novel distributed computing paradigm that supports the gathering, processing and analysis of high-volume, heterogeneous, continuous data streams, to extract insights and actionable results in real time. This comprehensive, hands-on guide combining the fundamental building blocks and emerging research in stream processing is ideal for application designers, system builders, analytic developers, as well as students and researchers in the field. This book introduces the key components of the stream computing paradigm, including the distributed system infrastructure, the programming model, design patterns and streaming analytics. The explanation of the underlying theoretical principles, illustrative examples and implementations using the IBM InfoSphere Streams SPL language and real-world case studies provide students and practitioners with a comprehensive understanding of such applications and the middleware that supports them.

Process algebra is a widely accepted and much used technique in the specification and verification of parallel and distributed software systems. This book sets the standard for the field. It assembles the relevant results of most process algebras currently in use, and presents them in a unified framework and notation. The authors describe the theory underlying the development, realization and maintenance of software that occurs in parallel or distributed systems. A system can be specified in the syntax provided, and the axioms can be used to verify that a composed system has the required external behaviour. As examples, two protocols are completely specified and verified in the text: the Alternating-Bit Protocol for Data Communication, and Fischer's Protocol of Mutual Exclusion. The book serves as a reference text for researchers and graduate students in computer science, offering a complete overview of the field and referring to further literature where appropriate.

For 80 years, mathematics has driven fundamental innovation in computing and communications. This timely book provides a panorama of some recent ideas in mathematics and how they will drive continued innovation in computing, communications and AI in the coming years. It provides a unique insight into how the new techniques that are being developed can be used to provide theoretical foundations for technological progress, just as mathematics was used in earlier times by Turing, von Neumann, Shannon and others. Edited by leading researchers in the field, chapters cover the application of new mathematics in computer architecture, software verification, quantum computing, compressed sensing, networking, Bayesian inference, machine learning, reinforcement learning and many other areas.

Communication complexity is the mathematical study of scenarios where several parties need to communicate to achieve a common goal, a situation that naturally appears during computation. This introduction presents the most recent developments in an accessible form, providing the language to unify several disjoint research subareas. Written as a guide for a graduate course on communication complexity, it will interest a broad audience in computer science, from advanced undergraduates to researchers in areas ranging from theory to algorithm design to distributed computing. The first part presents basic theory in a clear and illustrative way, offering beginners an entry into the field. The second part describes applications including circuit complexity, proof complexity, streaming algorithms, extension complexity of polytopes, and distributed computing. Proofs throughout the text use ideas from a wide range of mathematics, including geometry, algebra, and probability. Each chapter contain

This unified treatment of game theory focuses on finding state-of-the-art solutions to issues surrounding the next generation of wireless and communications networks. Future networks will rely on autonomous and distributed architectures to improve the efficiency and flexibility of mobile applications, and game theory provides the ideal framework for designing efficient and robust distributed algorithms. This book enables readers to develop a solid understanding of game theory, its applications and its use as an effective tool for addressing wireless communication and networking problems. The key results and tools of game theory are covered, as are various real-world technologies including 3G networks, wireless LANs, sensor networks, dynamic spectrum access and cognitive networks. The book also covers a wide range of techniques for modeling, designing and analysing communication networks using game theory, as well as state-of-the-art distributed design techniques. This is an ideal resou

The foundations of parallel computation, especially the efficiency of computation, are the concern of this book. Distinguished international researchers have contributed fifteen chapters which together form a coherent stream taking the reader who has little prior knowledge of the field to a position of being familiar with leading edge issues. The book may also function as a source of teaching material and reference for researchers. The first part is devoted to the Parallel Random Access Machine (P-RAM) model of parallel computation. The initial chapters justify and define the model, which is then used for the development of algorithm design in a variety of application areas such as deterministic algorithms, randomisation and algorithm resilience. The second part deals with distributed memory models of computation. The question of efficiently implementing P-RAM algorithms within these models is addressed as are the immensely interesting prospects for general purpose parallel computation

The TCP/IP family of protocols have become the de facto standard in the world of networking, are found in virtually all computer communication systems, and form the basis of today's Internet. TCP/IP Essentials is a hands-on guide to TCP/IP technologies, and shows how the protocols are implemented in practice. The book contains a series of extensively tested laboratory experiments that span the various elements of protocol definition and behavior. Topics covered include bridges, routers, LANs, static and dynamic routing, multicast and realtime service, and network management and security. The experiments are described in a Linux environment, with parallel notes on Solaris implementation. The book includes many homework exercises, and supplementary material for instructors is available. The book is aimed at students of electrical and computer engineering and students of computer science taking courses in networking. It is also an ideal guide for engineers studying for networking certific

The major reason for the lack of use of parallel computing is the mismatch between the complexity and variety of parallel hardware, and the software development tools to program it. The cost of developing software needs to be amortised over decades, but the platforms on which it executes change every few years, requiring complete rewrites. The evident cost-effectiveness of parallel computation has not been realized because of this mismatch. This book presents an integrated approach to parallel software development by addressing both software and performance issues together. It presents a methodology for software construction that produces architecture-independent and intellectually abstract software. The software can execute efficiently on a range of existing and potential hardware configurations. The approach is based on the construction of categorical data types, a generalization of abstract data types, and of objects. Categorical data types abstract both from the representation of a

Originally published in 2002, this book presents techniques in the application of formal methods to object-based distributed systems. A major theme of the book is how to formally handle the requirements arising from OO distributed systems, such as dynamic reconfiguration, encapsulation, subtyping, inheritance, and real-time aspects. These may be supported either by enhancing existing notations, such as UML, LOTOS, SDL and Z, or by defining fresh notations, such as Actors, Pi-calculus and Ambients. The major specification notations and modelling techniques are introduced and compared by leading researchers. The book also includes a description of approaches to the specification of non-functional requirements, and a discussion of security issues. Researchers and practitioners in software design, object-oriented computing, distributed systems, and telecommunications systems will gain an appreciation of the relationships between the major areas of concerns and learn how the use of object-o

Originally published in 2002, this book presents techniques in the application of formal methods to object-based distributed systems. A major theme of the book is how to formally handle the requirements arising from OO distributed systems, such as dynamic reconfiguration, encapsulation, subtyping, inheritance, and real-time aspects. These may be supported either by enhancing existing notations, such as UML, LOTOS, SDL and Z, or by defining fresh notations, such as Actors, Pi-calculus and Ambients. The major specification notations and modelling techniques are introduced and compared by leading researchers. The book also includes a description of approaches to the specification of non-functional requirements, and a discussion of security issues. Researchers and practitioners in software design, object-oriented computing, distributed systems, and telecommunications systems will gain an appreciation of the relationships between the major areas of concerns and learn how the use of object-o

Presenting the fundamentals of cooperative communications and networking, this book treats the concepts of space, time, frequency diversity and MIMO, with a holistic approach to principal topics where significant improvements can be obtained. Beginning with background and MIMO systems, Part I includes a review of basic principles of wireless communications and space-time diversity and coding. Part II then presents topics on physical layer cooperative communications such as relay channels and protocols, performance bounds, multi-node cooperation, and energy efficiency. Finally, Part III focuses on cooperative networking including cooperative and content-aware multiple access, distributed routing, source-channel coding, and cooperative OFDM. Including end-of-chapter review questions, this text will appeal to graduate students of electrical engineering and is an ideal textbook for advanced courses on wireless communications. It will also be of great interest to practitioners in the wirele

This book presents an easy-to-read discussion of domain decomposition algorithms, their implementation and analysis. The relationship between domain decomposition and multigrid methods is carefully explained at an elementary level, and discussions of the implementation of domain decomposition methods on massively parallel super computers are also included. All algorithms are fully described and explained, and a mathematical framework for the analysis and complete understanding of the methods is also carefully developed. In addition, numerous numerical examples are included to demonstrate the behaviour of this important class of numerical methods. This book is ideal for graduate students about to embark on a career in computational science. It will also be a valuable resource for all those interested in parallel computing and numerical computational methods.

In 1989, Michael Rabin proposed a fundamentally new approach to the problems of fault-tolerant routing and memory management in parallel computation, based on the idea of information dispersal. Yuh-Dauh Lyuu developed this idea in a number of new and exciting ways in his PhD thesis. Further work has led to extensions of these methods to other applications such as shared memory emulations. This volume presents an extended and updated printing of Lyuu's thesis. It gives a detailed treatment of the information dispersal approach to the problems of fault-tolerance and distributed representations of information which have resisted rigorous analysis by previous methods.

Originally published in 1993, this book was the first to offer a comprehensive review of large eddy simulations (LES) - the history, state of the art, and promising directions for research. Among topics covered are fundamentals of LES; LES of incompressible, compressible, and reacting flows; LES of atmospheric, oceanic, and environmental flows; and LES and massivelt parallel computing. The book grew out of an international workshop that, for the first time, brought together leading researchers in engineering and geophysics to discuss developments and applications of LES models in their respective fields. It will be of value to anyone with an interest in turbulence modelling.

Do you have the tools to address recent challenges and problems in modern computer networks? Discover a unified view of auction theoretic applications and develop auction models, solution concepts, and algorithms with this multidisciplinary review. Devise distributed, dynamic, and adaptive algorithms for ensuring robust network operation over time-varying and heterogeneous environments, and for optimizing decisions about services, resource allocation, and usage of all network entities. Topics including cloud networking models, MIMO, mmWave communications, 5G, data aggregation, task allocation, user association, interference management, wireless caching, mobile data offloading, and security. Introducing fundamental concepts from an engineering perspective and describing a wide range of state-of-the-art techniques, this is an excellent resource for graduate and senior undergraduate students, network and software engineers, economists, and researchers.

First published in 1976, this monograph presents an exposition of some of the more important theoretical and computational techniques that have been developed for the determination and interpretation of molecular wave functions. Although a comprehensive theory of the electronic structure and bonding in molecules had been developed by 1960, only with the advent of the electronic computer in the late 1950s did it become possible to perform accurate non-empirical calculations for molecules of chemical interest; indeed, much of the subsequent evolution of the theory has occurred in parallel with the development of computing machines and techniques.

Wireless sensor networks are set to play a key role in a wide range of civilian and military applications, with tiny sensors connected through wireless links performing various sensing, computing, communication, and control tasks in highly distributed systems. This book presents a critical element in the deployment of wireless sensor networks: the process of synchronization. It summarizes the most important clock synchronization protocols proposed for wireless sensor networks with special emphasis placed on deriving efficient clock offset estimation schemes and performance benchmarks. Graduate students of electrical and computer engineering and computer science will find this a valuable resource, as will engineers who are interested in designing efficient clock synchronization algorithms and improving the performance of existing synchronization protocols.

Concurrent Programming in ML focuses on the practical use of concurrency to implement naturally concurrent applications. In addition to a tutorial introduction to programming in Concurrent ML (CML), the book presents three extended examples using CML for practical systems programming: a parallel software build system, a simple concurrent window manager, and an implementation of distributed tuple spaces. CML, which is included as part of the SML of New Jersey (SML/NJ) distribution, combines the best features of concurrent programming and functional programming. This book also illustrates advanced SML programming techniques, and includes a chapter on the implementation of concurrency using features provided by the SML/NJ system. It will be of interest to programmers, students, and professional researchers working in computer language development.

Concurrent Programming in ML focuses on the practical use of concurrency to implement naturally concurrent applications. In addition to a tutorial introduction to programming in Concurrent ML (CML), the book presents three extended examples using CML for practical systems programming: a parallel software build system, a simple concurrent window manager, and an implementation of distributed tuple spaces. CML, which is included as part of the SML of New Jersey (SML/NJ) distribution, combines the best features of concurrent programming and functional programming. This book also illustrates advanced SML programming techniques, and includes a chapter on the implementation of concurrency using features provided by the SML/NJ system. It will be of interest to programmers, students, and professional researchers working in computer language development.

Games provide mathematical models for interaction. Numerous tasks in computer science can be formulated in game-theoretic terms. This fresh and intuitive way of thinking through complex issues reveals underlying algorithmic questions and clarifies the relationships between different domains. This collection of lectures, by specialists in the field, provides an excellent introduction to various aspects of game theory relevant for applications in computer science that concern program design, synthesis, verification, testing and design of multi-agent or distributed systems. Originally devised for a Spring School organised by the GAMES Networking Programme in 2009, these lectures have since been revised and expanded, and range from tutorials concerning fundamental notions and methods to more advanced presentations of current research topics. This volume is a valuable guide to current research on game-based methods in computer science for undergraduate and graduate students. It will also in