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Fog Data Analytics for IoT Applications

Next Generation Process Model with State of the Art Technologies

  • Book
  • © 2020

Overview

Editors:
  1. Sudeep Tanwar

    1. Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, India

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  • Presents case studies to demonstrate the process model for tackling future challenges associated with FDA
  • Discusses the layered architecture of FDA and also compares the life cycle of both big data and FDA
  • Focuses on FDA in IoT and requirements related to Industry 4.0

Part of the book series: Studies in Big Data (SBD, volume 76)

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Table of contents (20 chapters)

  1. Front Matter

    Pages i-xv
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  2. Introduction and Background of FDA

    1. Front Matter

      Pages 1-1
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    2. Introduction

      • Aparna Kumari, Rajesh Gupta, Sudeep Tanwar
      Pages 3-17

    3. Introduction to Fog Data Analytics for IoT Applications

      • Puneet Kansal, Dilip Sharma, Manoj Kumar
      Pages 19-38

    4. Fog Data Analytics: Systematic Computational Classification and Procedural Paradigm

      • D. Pradeep Kumar, R. Hanumantharaju, B. J. Sowmya, K. N. Shreenath, K. G. Srinivasa
      Pages 39-58

    5. Fog Computing: Building a Road to IoT with Fog Analytics

      • Avinash Kaur, Parminder Singh, Anand Nayyar
      Pages 59-78

    6. Data Collection in Fog Data Analytics

      • S. R. Mani Sekhar, Snehil Tewari, Haaris Rahman, G. M. Siddesh
      Pages 79-104

  3. Emerging Technologies and Architecture for FDA

    1. Front Matter

      Pages 105-105
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    2. Mobile FOG Architecture Assisted Continuous Acquisition of Fetal ECG Data for Efficient Prediction

      • Anupam Bhardwaj, Pooja Khanna, Sachin Kumar
      Pages 107-122

    3. Proposed Framework for Fog Computing to Improve Quality-of-Service in IoT Applications

      • Rakhi Akhare, Monika Mangla, Sanjivani Deokar, Vaishali Wadhwa
      Pages 123-143

    4. Fog Data Based Statistical Analysis to Check Effects of Yajna and Mantra Science: Next Generation Health Practices

      • Rohit Rastogi, Mamta Saxena, D. K. Chaturvedi, Santosh Satya, Navneet Arora, Mayank Gupta et al.
      Pages 145-172

  4. Role of IoT in FDA

    1. Front Matter

      Pages 173-173
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    2. Process Model for Fog Data Analytics for IoT Applications

      • Anjali Modi, Shreena Jani, Karansingh Chauhan, Jitendra Bhatia
      Pages 175-198

    3. Medical Analytics Based on Artificial Neural Networks Using Cognitive Internet of Things

      • Himani Bedekar, Gahangir Hossain, Ayush Goyal
      Pages 199-262

    4. Application of IoT-Based Smart Devices in Health Care Using Fog Computing

      • Satyasundara Mahapatra, Anupam Singh
      Pages 263-278

    5. Data Reduction Techniques in Fog Data Analytics for IoT Applications

      • Srinidhi Hiriyannaiah, Zaifa Khan, Aniket Singh, G. M. Siddesh, K. G. Srinivasa
      Pages 279-309

  5. Security Issues, Research Challenges, and Opportunities

    1. Front Matter

      Pages 311-311
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    2. Background and Research Challenges for Fog Data Analytics and IoT

      • Ansh Riyal, Geetansh Kumar, Deepak Kumar Sharma
      Pages 313-340

    3. Behavior-Based Approach for Fog Data Analytics: An Approach Toward Security and Privacy

      • Urvashi, Lalit K. Awasthi, Geeta Sikka
      Pages 341-354

    4. Data Security and Privacy Functions in Fog Data Analytics

      • Apoorva Bhagat, Srishty Mittal, Uzma Faiz, Deepak Kumar Sharma
      Pages 355-385
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Keywords

About this book

This book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. The exponential increase in sensors and smart gadgets (collectively referred as smart devices or Internet of things (IoT) devices) has generated significant amount of heterogeneous and multimodal data, known as big data. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud. Current research and development efforts generally focus on big data analytics and overlook the difficulty of facilitating fog data analytics (FDA). This book presents a model that addresses various research challenges, such as accessibility, scalability, fog nodes communication, nodal collaboration, heterogeneity, reliability, and quality of service (QoS) requirements, and includes case studies demonstrating its implementation. Focusing on FDAin IoT and requirements related to Industry 4.0, it also covers all aspects required to manage the complexity of FDA for IoT applications and also develops a comprehensive taxonomy.

Editors and Affiliations

  • Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, India

    Sudeep Tanwar

About the editor

Dr. Sudeep Tanwar is an Associate Professor at the Computer Engineering Department at the Institute of Technology of Nirma University, India, and was a Visiting Professor at Jan Wyzykowski University in Polkowice, Poland, and the University of Pitesti, Romani. He received his Ph.D. in Wireless Sensor Networks from the Faculty of Engineering and Technology, Mewar University, India, in 2016. He has received three best research paper awards, including two from top-tier international conferences (IEEE-ICC and IEEE-GLOBECOM). His current interests include routings issues in WSN, blockchain technology, smart grid, and fog computing. He has authored/edited six books: Routing in Heterogeneous Wireless Sensor Networks (ISBN: 978-3-330-02892-0), Big Data Analytics (ISBN: 978-93-83992-25-8), Mobile Computing (ISBN: 978-93-83992-25-6), Energy Conservation for IoT Devices: Concepts, Paradigms and Solutions (ISBN: 978-981-13-7398-5), and Multimedia Big Data Computing for IoT Applications: Concepts, Paradigms and Solutions (ISBN: 978-981-13-8759-3). He is an Associate Editor of the Security and Privacy Journal and is a member of IAENG, ISTE, and CSTA.​

Bibliographic Information

  • Book Title: Fog Data Analytics for IoT Applications

  • Book Subtitle: Next Generation Process Model with State of the Art Technologies

  • Editors: Sudeep Tanwar

  • Series Title: Studies in Big Data

  • DOI: https://doi.org/10.1007/978-981-15-6044-6

  • Publisher: Springer Singapore

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

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020

  • Hardcover ISBN: 978-981-15-6043-9Published: 26 August 2020

  • Softcover ISBN: 978-981-15-6046-0Published: 26 August 2021

  • eBook ISBN: 978-981-15-6044-6Published: 25 August 2020

  • Series ISSN: 2197-6503

  • Series E-ISSN: 2197-6511

  • Edition Number: 1

  • Number of Pages: XV, 497

  • Number of Illustrations: 37 b/w illustrations, 172 illustrations in colour

  • Topics: Computational Intelligence, Big Data, Big Data/Analytics, Information Systems Applications (incl. Internet)

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