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Sublinear Algorithms for Big Data Applications

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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.

Author(s): Dan Wang, Zhu Han
Series: SpringerBriefs in Computer Science
Edition: 2015
Publisher: Springer International Publishing
Year: 2015

Language: English
Pages: 85
Tags: Database Management; Computer Communication Networks; Communications Engineering, Networks

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