Springerbriefs in Computer Science

By: Dan Wang, Zhu Han

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Paperback | 20 August 2015

At a Glance

Paperback
100 Pages

Dimensions(cm)
22.86 x 15.24 x 0.64

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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.

Industry Reviews

"Wang and Han's book focuses on sublinear algorithms for processing big data. ... For the researcher, this book also shows that there is room for improvement and new discoveries in this flourishing area. ... The book is thus recommended mainly to researchers, but just as a piece of the bigger puzzle of sublinear algorithms for big data processing and applications." (Corrado Mencar, Computing Reviews, computingreviews.com, August, 2016)

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