Sublinear Algorithms for Big Data Applications

1. Front Matter

   Pages i-xi

   PDF

2. Introduction

   • Dan Wang, Zhu Han

   Pages 1-7

3. Basics for Sublinear Algorithms

   • Dan Wang, Zhu Han

   Pages 9-21

4. Application on Wireless Sensor Networks

   • Dan Wang, Zhu Han

   Pages 23-46

5. Application on Big Data Processing

   • Dan Wang, Zhu Han

   Pages 47-67

6. Application on a Smart Grid

   • Dan Wang, Zhu Han

   Pages 69-82

7. Concluding Remarks

   • Dan Wang, Zhu Han

   Pages 83-85

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.

• Big data applications
• Big data processing
• Smart grids
• Sublinear algorithms
• Wireless sensor networks

“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)

• Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR

  Dan Wang

• Department of Engineering, University of Houston, Houston, USA

  Zhu Han

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