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.
Stochastic processes are found in probabilistic systems that evolve with time. Discrete stochastic processes change by only integer time steps (for some time scale), or are characterized by discrete occurrences at arbitrary times. Discrete Stochastic Processes helps the reader develop the understanding and intuition necessary to apply stochastic process theory in engineering, science and operations research. The book approaches the subject via many simple examples which build insight into the structure of stochastic processes and the general effect of these phenomena in real systems. The book presents mathematical ideas without recourse to measure theory, using only minimal mathematical analysis. In the proofs and explanations, clarity is favored over formal rigor, and simplicity over generality. Numerous examples are given to show how results fail to hold when all the conditions are not satisfied. Audience: An excellent textbook for a graduate level course in engineering and operations research. Also an invaluable reference for all those requiring a deeper understanding of the subject.
Information, Coding and Mathematics is a classic reference for both professional and academic researchers working in error-correction coding and decoding, Shannon theory, cryptography, digital communications, information security, and electronic engineering. The work represents a collection of contributions from leading experts in turbo coding, cryptography and sequences, Shannon theory and coding bounds, and decoding theory and applications. All of the contributors have individually and collectively dedicated their work as a tribute to the outstanding work of Robert J. McEliece. Information, Coding and Mathematics covers the latest advances in the widely used and rapidly developing field of information and communication technology.
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