Big Data Concepts, Theories, and Applications

  • Shui Yu
  • Song Guo

Table of contents

  1. Front Matter
    Pages i-viii
  2. Genoveva Vargas-Solar, Javier A. Espinosa-Oviedo, José Luis Zechinelli-Martini
    Pages 1-27
  3. Sourav Mazumder
    Pages 29-128
  4. Binfeng Wang, Jun Zhang, Zili Zhang, Wei Luo, Dawen Xia
    Pages 129-156
  5. Lei Xu, Weidong Shi
    Pages 157-192
  6. Xiaokui Shu, Fang Liu, Danfeng (Daphne) Yao
    Pages 193-235
  7. Mi Wen, Shui Yu, Jinguo Li, Hongwei Li, Kejie Lu
    Pages 237-255
  8. Shuyu Li, Jerry Gao
    Pages 281-313
  9. Kok-Leong Ong, Daswin De Silva, Yee Ling Boo, Ee Hui Lim, Frank Bodi, Damminda Alahakoon et al.
    Pages 315-351
  10. Athanasios Karmas, Angelos Tzotsos, Konstantinos Karantzalos
    Pages 353-390
  11. Bin Fang, Peng Zhang
    Pages 391-412
  12. Sien Chen, Yinghua Huang, Wenqiang Huang
    Pages 413-437

About this book


This book covers three major parts of Big Data: concepts, theories and applications. Written by world-renowned leaders in Big Data, this book explores the problems, possible solutions and directions for Big Data in research and practice.  It also focuses on high level concepts such as definitions of Big Data from different angles; surveys in research and applications; and existing tools, mechanisms, and systems in practice. Each chapter is independent from the other chapters, allowing users to read any chapter directly.

After examining the practical side of Big Data, this book presents theoretical perspectives. The theoretical research ranges from Big Data representation, modeling and topology to distribution and dimension reducing.  Chapters also investigate the many disciplines that involve Big Data, such as statistics, data mining, machine learning, networking, algorithms, security and differential geometry. The last section of this book introduces Big Data applications from different communities, such as business, engineering and science.

Big Data Concepts, Theories and Applications is designed as a reference for researchers and advanced level students in computer science, electrical engineering and mathematics. Practitioners who focus on information systems, big data, data mining, business analysis and other related fields will also find this material valuable. 


Big data Big data applications Cryptographic algorithms Data mining Data security Massive data streaming Mathematical modeling Mobile entertainment Mobile gaming Mobile networks Mobile social networks Queuing modeling Smart city Social networks Theoretical modeling Traffic classification

Editors and affiliations

  • Shui Yu
    • 1
  • Song Guo
    • 2
  1. 1.School of Information TechnologyDeakin UniversityBurwoodAustralia
  2. 2.Schl of Comp Science & EnggThe Univ of AizuAizu-Wakamatsu CityJapan

Bibliographic information