Sublinear algorithms for big data applications / Dan Wang, Zhu Han. [electronic resource]
2015
QA76.9.A43 W35 2015eb
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Title
Sublinear algorithms for big data applications / Dan Wang, Zhu Han. [electronic resource]
ISBN
9783319204482 electronic book
3319204483 electronic book
9783319204475
3319204483 electronic book
9783319204475
Published
Cham : Springer, 2015.
Language
English
Description
1 online resource (xi, 85 pages) : illustrations.
Call Number
QA76.9.A43 W35 2015eb
Dewey Decimal Classification
005.1
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.
Bibliography, etc. Note
Includes bibliographical references.
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Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed July 22, 2015).
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Series
SpringerBriefs in computer science.
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Table of Contents
Introduction
Basics for Sublinear Algorithms
Applications for Wireless Sensor Networks
Applications for Big Data Processing
Applications for a Smart Grid
Concluding Remarks.
Basics for Sublinear Algorithms
Applications for Wireless Sensor Networks
Applications for Big Data Processing
Applications for a Smart Grid
Concluding Remarks.