Guide To Distributed Algorithms
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Distributed Algorithms
Author: Özalp Babaoglu
language: en
Publisher: Springer Science & Business Media
Release Date: 1996-09-25
Microsystem technology (MST) integrates very small (up to a few nanometers) mechanical, electronic, optical, and other components on a substrate to construct functional devices. These devices are used as intelligent sensors, actuators, and controllers for medical, automotive, household and many other purposes. This book is a basic introduction to MST for students, engineers, and scientists. It is the first of its kind to cover MST in its entirety. It gives a comprehensive treatment of all important parts of MST such as microfabrication technologies, microactuators, microsensors, development and testing of microsystems, and information processing in microsystems. It surveys products built to date and experimental products and gives a comprehensive view of all developments leading to MST devices and robots.
Distributed Algorithms
In Distributed Algorithms, Nancy Lynch provides a blueprint for designing, implementing, and analyzing distributed algorithms. She directs her book at a wide audience, including students, programmers, system designers, and researchers. Distributed Algorithms contains the most significant algorithms and impossibility results in the area, all in a simple automata-theoretic setting. The algorithms are proved correct, and their complexity is analyzed according to precisely defined complexity measures. The problems covered include resource allocation, communication, consensus among distributed processes, data consistency, deadlock detection, leader election, global snapshots, and many others. The material is organized according to the system model—first by the timing model and then by the interprocess communication mechanism. The material on system models is isolated in separate chapters for easy reference. The presentation is completely rigorous, yet is intuitive enough for immediate comprehension. This book familiarizes readers with important problems, algorithms, and impossibility results in the area: readers can then recognize the problems when they arise in practice, apply the algorithms to solve them, and use the impossibility results to determine whether problems are unsolvable. The book also provides readers with the basic mathematical tools for designing new algorithms and proving new impossibility results. In addition, it teaches readers how to reason carefully about distributed algorithms—to model them formally, devise precise specifications for their required behavior, prove their correctness, and evaluate their performance with realistic measures.
Guide to Distributed Algorithms
The study of distributed algorithms provides the needed background in many real-life applications, such as: distributed real-time systems, wireless sensor networks, mobile ad hoc networks and distributed databases. The main goal of Guide to Distributed Algorithms is to provide a detailed study of the design and analysis methods of distributed algorithms and to supply the implementations of most of the presented algorithms in Python language, which is the unique feature of the book not found in any other contemporary books on distributed computing. Topics and features: Presents comprehensive design methods for distributed algorithms Provides detailed analysis for the algorithms presented Uses graph templates to demonstrate the working of algorithms Provides working Python code for most of the algorithms presented This unique textbook/study manual can serve as a comprehensive manual of distributed algorithms for Computer Science and non-CS majors as well as practitioners of distributed algorithms in research projects.