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Sublinear Algorithms for Big Data Applications

  • Book
  • © 2015

Overview

Authors:
  1. Dan Wang

    1. Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR

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    You can also search for this author in PubMed   Google Scholar

  2. Zhu Han

    1. Department of Engineering, University of Houston, Houston, USA

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    You can also search for this author in PubMed   Google Scholar

Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-xi
    Download chapter 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
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Keywords

About this book

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.

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)

Authors and Affiliations

  • 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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