Distributed algorithms have been the subject of intense development over the last twenty years. The second edition of this successful textbook provides an up-to-date introduction both to the topic, and to the theory behind the algorithms. The clear presentation makes the book suitable for advanced undergraduate or graduate courses, whilst the coverage is sufficiently deep to make it useful for practising engineers and researchers. The author concentrates on algorithms for the point-to-point message passing model, and includes algorithms for the implementation of computer communication networks. Other key areas discussed are algorithms for the control of distributed applications (wave, broadcast, election, termination detection, randomized algorithms for anonymous networks, snapshots, deadlock detection, synchronous systems), and fault-tolerance achievable by distributed algorithms. The two new chapters on sense of direction and failure detectors are state-of-the-art and will provide an entry to research in these still-developing topics.

An Introduction to Distributed Algorithms takes up some of the main concepts and algorithms, ranging from basic to advanced techniques and applications, that underlie the programming of distributed-memory systems such as computer networks, networks of work-stations, and multiprocessors. Written from the broad perspective of distributed-memory systems in general it includes topics such as algorithms for maximum flow, programme debugging, and simulation that do not appear in more orthodox texts on distributed algorithms.

The new edition of a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. This book offers students and researchers a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. It avoids mathematical argumentation, often a stumbling block for students, teaching algorithmic thought rather than proofs and logic. This approach allows the student to learn a large number of algorithms within a relatively short span of time. Algorithms are explained through brief, informal descriptions, illuminating examples, and practical exercises. The examples and exercises allow readers to understand algorithms intuitively and from different perspectives. Proof sketches, arguing the correctness of an algorithm or explaining the idea behind fundamental results, are also included. The algorithms presented in the book are for the most part “classics,” selected because they shed light on the algorithmic design of distributed systems or on key issues in distributed computing and concurrent programming. This second edition has been substantially revised. A new chapter on distributed transaction offers up-to-date treatment of database transactions and the important evolving area of transactional memory. A new chapter on security discusses two exciting new topics: blockchains and quantum cryptography. Sections have been added that cover such subjects as rollback recovery, fault-tolerant termination detection, and consensus for shared memory. An appendix offers pseudocode descriptions of many algorithms. Solutions and slides are available for instructors. Distributed Algorithms can be used in courses for upper-level undergraduates or graduate students in computer science, or as a reference for researchers in the field.

This text is based on a simple and fully reactive computational model that allows for intuitive comprehension and logical designs. The principles and techniques presented can be applied to any distributed computing environment (e.g., distributed systems, communication networks, data networks, grid networks, internet, etc.). The text provides a wealth of unique material for learning how to design algorithms and protocols perform tasks efficiently in a distributed computing environment.

Distributed computing is at the heart of many applications. It arises as soon as one has to solve a problem in terms of entities -- such as processes, peers, processors, nodes, or agents -- that individually have only a partial knowledge of the many input parameters associated with the problem. In particular each entity cooperating towards the common goal cannot have an instantaneous knowledge of the current state of the other entities. Whereas parallel computing is mainly concerned with 'efficiency', and real-time computing is mainly concerned with 'on-time computing', distributed computing is mainly concerned with 'mastering uncertainty' created by issues such as the multiplicity of control flows, asynchronous communication, unstable behaviors, mobility, and dynamicity. While some distributed algorithms consist of a few lines only, their behavior can be difficult to understand and their properties hard to state and prove. The aim of this book is to present in a comprehensive way the basic notions, concepts, and algorithms of distributed computing when the distributed entities cooperate by sending and receiving messages on top of an asynchronous network. The book is composed of seventeen chapters structured into six parts: distributed graph algorithms, in particular what makes them different from sequential or parallel algorithms; logical time and global states, the core of the book; mutual exclusion and resource allocation; high-level communication abstractions; distributed detection of properties; and distributed shared memory. The author establishes clear objectives per chapter and the content is supported throughout with illustrative examples, summaries, exercises, and annotated bibliographies. This book constitutes an introduction to distributed computing and is suitable for advanced undergraduate students or graduate students in computer science and computer engineering, graduate students in mathematics interested in distributed computing, and practitioners and engineers involved in the design and implementation of distributed applications. The reader should have a basic knowledge of algorithms and operating systems.

This clearly structured textbook/reference presents a detailed and comprehensive review of the fundamental principles of sequential graph algorithms, approaches for NP-hard graph problems, and approximation algorithms and heuristics for such problems. The work also provides a comparative analysis of sequential, parallel and distributed graph algorithms – including algorithms for big data – and an investigation into the conversion principles between the three algorithmic methods. Topics and features: presents a comprehensive analysis of sequential graph algorithms; offers a unifying view by examining the same graph problem from each of the three paradigms of sequential, parallel and distributed algorithms; describes methods for the conversion between sequential, parallel and distributed graph algorithms; surveys methods for the analysis of large graphs and complex network applications; includes full implementation details for the problems presented throughout the text; provides additional supporting material at an accompanying website. This practical guide to the design and analysis of graph algorithms is ideal for advanced and graduate students of computer science, electrical and electronic engineering, and bioinformatics. The material covered will also be of value to any researcher familiar with the basics of discrete mathematics, graph theory and algorithms.

Algorithms and Theory of Computation Handbook, Second Edition: Special Topics and Techniques provides an up-to-date compendium of fundamental computer science topics and techniques. It also illustrates how the topics and techniques come together to deliver efficient solutions to important practical problems.Along with updating and revising many of

Topics on the Dynamics of Civil Structures, Volume 1, Proceedings of the 30th IMAC, A Conference and Exposition on Structural Dynamics, 2012, the first volume of six from the Conference, brings together 45 contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Human Induced Vibrations Bridge Dynamics Operational Modal Analysis Experimental Techniques and Modeling for Civil Structures System Identification for Civil Structures Method and Technologies for Bridge Monitoring Damage Detection for Civil Structures Structural Modeling Vibration Control Method and Approaches for Civil Structures Modal Testing of Civil Structures

This volume contains the proceedings of the 4th International Workshop on Distributed Algorithms, held near Bari, Italy, September 24-26, 1990. The workshop was a forum for researchers, students and other interested persons to discuss recent results and trends in the design and analysis of distributed algorithms for communication networks and decentralized systems. The volume includes all 28 papers presented at the workshop, covering current research in such aspects of distributed algorithm design as distributed combinatorial algorithms, distributed algorithms on graphs, distributed algorithms for new types of decentralized systems, distributed data structures, synchronization and load-balancing, distributed algorithms for control and communication, design and verification of network protocols, routing algorithms, fail-safe and fault-tolerant distributed algorithms, distributed database techniques, algorithms for transaction management and replica control, and other related topics.