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Fog Computing, Deep Learning and Big Data Analytics-Research Directions

Authors:

  • Provides a comprehensive overview of fog computing technology
  • Explores research issues involved in the application of traditional shallow machine learning and deep learning techniques to big data analytics
  • Identifies several unsolved research problems and research directions in fog computing

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-xiii
  2. Introduction

    • C. S. R. Prabhu
    Pages 1-20
  3. Fog Application Management

    • C. S. R. Prabhu
    Pages 21-24
  4. Fog Analytics

    • C. S. R. Prabhu
    Pages 25-42
  5. Fog Security and Privacy

    • C. S. R. Prabhu
    Pages 43-46
  6. Research Directions

    • C. S. R. Prabhu
    Pages 47-55
  7. Conclusion

    • C. S. R. Prabhu
    Pages 57-57
  8. Back Matter

    Pages 59-71

About this book

This book provides a comprehensive picture of fog computing technology, including of fog architectures, latency aware application management issues with real time requirements, security and privacy issues and fog analytics, in wide ranging application scenarios such as M2M device communication, smart homes, smart vehicles, augmented reality and transportation management.
 
This book explores the research issues involved in the application of traditional shallow machine learning and deep learning techniques to big data analytics. It surveys global research advances in extending the conventional unsupervised or clustering algorithms, extending supervised and semi-supervised algorithms and association rule mining algorithms to big data Scenarios. Further it discusses the deep learning applications of big data analytics to fields of computer vision and speech processing, and describes applications such as semantic indexing and data tagging. Lastly it identifies 25 unsolved research problems and research directions in fog computing, as well as in the context of applying deep learning techniques to big data analytics, such as dimensionality reduction in high-dimensional data and improved formulation of data abstractions along with possible directions for their solutions.

Authors and Affiliations

  • National Informatics Centre (NIC) (Retd.), Ministry of Electronics and Information Technology, Government of India, New Delhi, India

    C.S.R. Prabhu

About the author

Dr. Chivukula Sree Rama Prabhu has held prestigious positions with Government of India and various Institutions. He retired as the Director General of National Informatics Centre (NIC) Ministry of Electronics and Information Technology Government of India, New Delhi, and has worked in various capacities at Tata Consultancy Services (TCS), CMC, TES and TELCO (now Tata Motors). He was also an international resource faculty for the Programs of APO (Asian Productivity Organization), and represented India on the International Panel at Venture 2004 held by APO at Osaka, Japan. He taught and researched at the University of Central Florida, Orlando and also had a brief stint as a Consultant to NASA Cape Canaveral.

 
Mr. Prabhu was unanimously elected and served as the Chairman of Computer Society of India (CSI), Hyderabad Chapter. He is presently working as an Advisor at KL University, Vijayawada, Andhra Pradesh and as a Director, Research and Innovation at Keshav Memorial Institute of Technology (KMIT), Hyderabad.
 
He obtained his master’s degree in Electrical Engineering with specialization in Computer Science from the Indian Institute of Technology, Bombay after a bachelor’s degree in Electronics and Communication Engineering from Jawaharlal Nehru Technological University, Hyderabad in 1976. He has guided a large number of student research projects at master’s level and has published several papers.




Bibliographic Information

  • Book Title: Fog Computing, Deep Learning and Big Data Analytics-Research Directions

  • Authors: C.S.R. Prabhu

  • DOI: https://doi.org/10.1007/978-981-13-3209-8

  • Publisher: Springer Singapore

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Nature Singapore Pte Ltd. 2019

  • Hardcover ISBN: 978-981-13-3208-1Published: 16 January 2019

  • eBook ISBN: 978-981-13-3209-8Published: 04 January 2019

  • Edition Number: 1

  • Number of Pages: XIII, 71

  • Number of Illustrations: 4 b/w illustrations, 1 illustrations in colour

  • Topics: Big Data, Data Structures, Computer Appl. in Administrative Data Processing

Buy it now

Buying options

eBook USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access