PDF Ebook Distributed Computing: A Locality-Sensitive Approach (Monographs on Discrete Mathematics and Applications), by David Peleg
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Distributed Computing: A Locality-Sensitive Approach (Monographs on Discrete Mathematics and Applications), by David Peleg
PDF Ebook Distributed Computing: A Locality-Sensitive Approach (Monographs on Discrete Mathematics and Applications), by David Peleg
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This volume presents the locality-sensitive approach to distributed network algorithms-the utilization of locality to simplify control structures and algorithms and reduce their costs. The author begins with an introductory exposition of distributed network algorithms focusing on topics that illustrate the role of locality in distributed algorithmic techniques. He then introduces locality-preserving network representations and describes sequential and distributed techniques for their construction. Finally, the applicability of the locality-sensitive approach is demonstrated through several applications. Distributed Computing: A Locality-Sensitive Approach is the only book that gives a thorough exposition of network spanners and other locality-preserving network representations such as sparse covers and partitions. The book is useful for computer scientists interested in distributed computing, electrical engineers interested in network architectures and protocols, and for discrete mathematicians and graph theorists.
- Sales Rank: #523350 in Books
- Brand: Society for Industrial & Applied Mathematics,U.S.
- Published on: 1987-01-01
- Ingredients: Example Ingredients
- Original language: English
- Number of items: 1
- Dimensions: 8.98" h x .94" w x 5.98" l, 1.87 pounds
- Binding: Hardcover
- 359 pages
About the Author
David Peleg is the Norman D. Cohen Professorial Chair of Computer Sciences at the Weizmann Institute of Science, Rehovot, Israel.
Most helpful customer reviews
0 of 0 people found the following review helpful.
This book is excellent for learning about sparse covers and partitions
By Konstantin
This book is excellent for learning about sparse covers and partitions, which are fundamental concepts for many other algorithms. Well written, clear with a good variety of topics.
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