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 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.
A comprehensive guide to distributed algorithms that emphasizes examples and exercises rather than mathematical argumentation. 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. An appendix offers pseudocode descriptions of many algorithms. Distributed algorithms are performed by a collection of computers that send messages to each other or by multiple software threads that use the same shared memory. 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. 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.
There are many benefits of solving problems in a decentralized manner. Distributed algorithms often do not require global information which can alleviate the curse of dimensionality in large networks, there is often robustness to failure of parts, and they are often more robust to failure of parts, and to dynamic changes to the environment that can occur while maintaining performance. This dissertation will focus on three problems involving networked systems in which distributed algorithms have significant benefits: constrained load balancing, traffic congestion minimization, and traffic intersection efficiency. Many physical limitations of real systems are not considered in the literature of distributed load balancing algorithms. We address the specific problem of quantized distributed load balancing over a network of agents subject to upper-limit constraints. We then shift focus to traffic systems, where endowing traffic control systems with local information and communication can be exploited for further efficiency. Motivated by a desire to reduce congestion, we propose two distributed algorithms to reduce delays: a dynamic lane reversal algorithm and a rerouting algorithm. Finally, we present a novel intersection control algorithm based on an objective function that accounts for drivers' time preferences. For each problem, a specific objective is formed mathematically. An algorithm is designed to achieve this objective, and stability and convergence of the algorithms are analyzed. Experiments are run through simulation to verify stability and convergence as well as to test performance.
This classroom-tested textbook provides an accessible introduction to the design, formal modeling, and analysis of distributed computer systems. The book uses Maude, a rewriting logic-based language and simulation and model checking tool, which offers a simple and intuitive modeling formalism that is suitable for modeling distributed systems in an attractive object-oriented and functional programming style. Topics and features: introduces classical algebraic specification and term rewriting theory, including reasoning about termination, confluence, and equational properties; covers object-oriented modeling of distributed systems using rewriting logic, as well as temporal logic to specify requirements that a system should satisfy; provides a range of examples and case studies from different domains, to help the reader to develop an intuitive understanding of distributed systems and their design challenges; examples include classic distributed systems such as transport protocols, cryptographic protocols, and distributed transactions, leader election, and mutual execution algorithms; contains a wealth of exercises, including larger exercises suitable for course projects, and supplies executable code and supplementary material at an associated website. This self-contained textbook is designed to support undergraduate courses on formal methods and distributed systems, and will prove invaluable to any student seeking a reader-friendly introduction to formal specification, logics and inference systems, and automated model checking techniques.
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.
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.
