Sublinear Algorithms for Big Data Applications

by Dan Wang, Zhu Han

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 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.

151 pages, Kindle Edition

First published September 14, 2015

About the author

Dan Wang (王丹) is one of the students leaders in the 1989 pro-democracy movement in China, as well as a renowned poet.

While in China, Wang was sent to prison more than once for his beliefs and activism. Eventually paroled due to medical reasons, he went to the United States in 1998 and was accepted into Harvard, where he finished his masters and then Ph.D in East Asian history.