Sublinear Algorithms for Big Data Applications

✍ Scribed by Dan Wang, Zhu Han

Publisher: Springer International Publishing
Year: 2015
Tongue: English
Leaves: 94
Series: SpringerBriefs in Computer Science
Edition: 2015
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xi
Introduction....Pages 1-7
Basics for Sublinear Algorithms....Pages 9-21
Application on Wireless Sensor Networks....Pages 23-46
Application on Big Data Processing....Pages 47-67
Application on a Smart Grid....Pages 69-82
Concluding Remarks....Pages 83-85

✦ Subjects

Database Management; Computer Communication Networks; Communications Engineering, Networks

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