Data Networks: Second Edition

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Athena Scientific, Oct 2, 2021 - Technology & Engineering - 570 pages

This classic textbook aims to provide a fundamental understanding of the principles that underlie the design of data networks, which form the backbone of the modern internet. It was developed through classroom use at MIT in the 1980s, and continues to be used as a textbook in MIT classes. The present edition also contains detailed high-quality solutions to all the end-of-chapter exercises.

Among its major features the book:

1) Describes the principles of layered architectures. 2) Explains the principles of data link control, with many examples and insights into distributed algorithms and protocols. 3) Provides an intuitive coverage of queueing, and its applications in delay and performance analysis of networks. 4) Covers the theory of multiaccess communications and local data networks. 5) Discusses in-depth theoretical and practical aspects of routing and topological design. 6) Covers the theory of flow control, emphasizing issues of congestion and delay in integrated high-speed networks.


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Introduction and Layered Network Architecture
PointtoPoint Protocols and Links
Delay Models in Data Networks
Multiclass Communication
Routing in Data Networks
Flow Control
Solutions Manual
Chapter 1 Solutions
Chapter 2 Solutions
Chapter 3 Solutions
Chapter 4 Solutions
Chapter 5 Solutions
Chapter 6 Solutions

Common terms and phrases

About the author (2021)

Dimitri P. Bertsekas undergraduate studies were in engineering at the National Technical University of Athens, Greece. He obtained his MS in electrical engineering at the George Washington University, Wash. DC in 1969, and his Ph.D. in system science in 1971 at the Massachusetts Institute of Technology.

Dr. Bertsekas has held faculty positions with the Engineering-Economic Systems Dept., Stanford University (1971-1974) and the Electrical Engineering Dept. of the University of Illinois, Urbana (1974-1979). From 1979 to 2019 he was with the Electrical Engineering and Computer Science Department of the Massachusetts Institute of Technology (M.I.T.), where he served as McAfee Professor of Engineering. In 2019, he was appointed Fulton Professor of Computational Decision Making, and a full time faculty member at the department of Computer, Information, and Decision Systems Engineering at Arizona State University (ASU), Tempe, while maintaining a research position at MIT. His research spans several fields, including optimization, control, large-scale computation, and data communication networks, and is closely tied to his teaching and book authoring activities. He has written numerous research papers, and eighteen books and research monographs, several of which are used as textbooks in MIT and ASU classes. Most recently Dr Bertsekas has been focusing on reinforcement learning, and authored a textbook in 2019, and a research monograph on its distributed and multiagent implementation aspects in 2020.

Professor Bertsekas was awarded the INFORMS 1997 Prize for Research Excellence in the Interface Between Operations Research and Computer Science for his book "Neuro-Dynamic Programming", the 2000 Greek National Award for Operations Research, the 2001 ACC John R. Ragazzini Education Award, the 2009 INFORMS Expository Writing Award, the 2014 ACC Richard E. Bellman Control Heritage Award for "contributions to the foundations of deterministic and stochastic optimization-based methods in systems and control," the 2014 Khachiyan Prize for Life-Time Accomplishments in Optimization, the SIAM/MOS 2015 George B. Dantzig Prize, and the 2022 IEEE Control Systems Award. In 2018, he was awarded, jointly with his coauthor John Tsitsiklis, the INFORMS John von Neumann Theory Prize, for the contributions of the research monographs "Parallel and Distributed Computation" and "Neuro-Dynamic Programming". In 2001, he was elected to the United States National Academy of Engineering for "pioneering contributions to fundamental research, practice and education of optimization/control theory, and especially its application to data communication networks."

Dr. Bertsekas' recent books are "Introduction to Probability: 2nd Edition" (2008), "Convex Optimization Theory" (2009), "Dynamic Programming and Optimal Control," Vol. I, (2017), and Vol. II: (2012), "Abstract Dynamic Programming" (2018), "Convex Optimization Algorithms" (2015), "Reinforcement Learning and Optimal Control" (2019), and "Rollout, Policy Iteration, and Distributed Reinforcement Learning" (2020), all published by Athena Scientific.

Robert G. Gallager received the BSEE degree from the University of Pennsylvania in 1953, and the S.M. and Sc.D. degrees in electrical engineering from the Massachusetts Institute of Technology in 1957 and 1960, respectively. From 1953 to 1956, he was at Bell Telephone Laboratories and then the U.S. Signal Corps. He has been a faculty member at MIT since 1960, became Co-Director of the Laboratory for Information and Decision Systems in 1986, and Fujitsu Professor in 1988. His current title is Professor Emeritus.

In the mid 1970’s, Professor Gallager’s research focus shifted to data networks, focusing on distributed algorithms, routing, congestion control, and random access techniques. Data Networks, Prentice Hall, 1988, second edition 1992, co-authored with D. Bertsekas, helped provide a conceptual foundation for this field.In the mid 1970’s, Professor Gallager’s research focus shifted to data networks, focusing on distributed algorithms, routing, congestion control, and random access techniques. Data Networks, Prentice Hall, 1988, second edition 1992, co-authored with D. Bertsekas, helped provide a conceptual foundation for this field. His joint papers with Parekh, “A Generalized Processor Sharing Approach to Flow Control in ISN,” in 1993 won the William Bennett Prize Paper Award for 1993, and the Prize Paper Award for Infocomm 1993. Finally, his joint 1983 paper with P. Humblet and P Spira in ACM Trans.Prog. Lang. Sys. won the ACM 2004 Dijkstra Prize in Distributed Computing.

Professor Gallager was involved in the founding of Codex Corporation in 1962 (now part of Motorola) and consulted there for many years. His fundamental studies on quadrature amplitude modulation and detection led directly to the 9600 bps modems that provided Codex’s commercial success. He has also consulted for a number of other companies and has received 5 patents.

He was President of the Information Theory Society of the IEEE in 1971, Chairman of the Advisory committee to the NSF Division on Networking andCommunication Research and Infrastructure from 1989 to 1992, and has been on numerous visiting committees for Electrical Engineering and Computer Science departments. His honors, along with the prize paper awards above, include IEEE Fellow (1968), U. of Pa. Moore School Gold Medal Award (1973), Guggenheim Fellow (1978), National Academy of Engineering (1979), IEEE IT Soc. Shannon Award (1983), IEEE Centennial Medal (1984), IEEE Medal of Honor (1990), National Academy of Sciences (1992), Fellow of the American Academy of Arts and Sciences, (1999), The Harvey Prize in Science and Technology from Technion (1999), IEC Fellow (2000), IEEE Third Millenium Medal (2000), Eduard Rhein Award, (2002) and Marconi Fellow(2003) .

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