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Cover Art
E-RESOURCE
Author Wang, Dan (Computer scientist), author.

Title Sublinear algorithms for big data applications / Dan Wang, Zhu Han.

Published Cham : Springer, 2015.

Copies

Location Call No. Status
 UniM INTERNET resource    AVAILABLE
Physical description 1 online resource (xi, 85 pages) : illustrations (some color)
Series SpringerBriefs in computer science, 2191-5768
SpringerBriefs in computer science.
Springer English/International eBooks 2015 - Full Set
Bibliography Includes bibliographical references.
Contents Introduction -- Basics for Sublinear Algorithms -- Applications for Wireless Sensor Networks -- Applications for Big Data Processing -- Applications for a Smart Grid -- Concluding Remarks.
Summary The brief focuses on applying sublinear algorithms to manage critical big data challenges. The text offers an essential introduction to sublinear algorithms, explaining why they are vital to large scale data systems. It also demonstrates how to apply sublinear algorithms to three familiar big data applications: wireless sensor networks, big data processing in Map Reduce and smart grids. These applications present common experiences, bridging the theoretical advances of sublinear algorithms and the application domain. Sublinear Algorithms for Big Data Applications is suitable for researchers, engineers and graduate students in the computer science, communications and signal processing communities.
Other author Han, Zhu, 1974- author.
SpringerLink issuing body.
Subject Computer algorithms.
Big data.
Electronic books.
Electronic books.
ISBN 9783319204482
3319204483
9783319204475
3319204475 (print)
9783319204475 (print)
Standard Number 10.1007/978-3-319-20448-2