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Mobile Big Data

A Roadmap from Models to Technologies

  • Book
  • © 2018

Overview

Editors:
  1. Georgios Skourletopoulos

    1. Department of Computer Science, University of Nicosia, Nicosia, Cyprus

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  2. George Mastorakis

    1. Department of Business Administration, Technological Educational Institute Crete, Agios Nikolaos, Greece

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  3. Constandinos X. Mavromoustakis

    1. Department of Computer Science, University of Nicosia, Nicosia, Cyprus

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  4. Ciprian Dobre

    1. Department of Computer Science and Engineering, University Politehnica of Bucharest, Bucharest, Romania

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  5. Evangelos Pallis

    1. Department of Informatics Engineering, Technological Educational Institute of Crete, Crete, Greece

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  • Provides a state-of-the-art reference guide, discussing the progress made, as well as outlining future directions for the theories, practices, standards, and strategies related to the mobile big data domain
  • Targets methodologies designed to take mobile big data to the Cloud, and to enable processing real-time streaming of events on-the-move
  • Discusses methods and practices to improve multisource big data collection techniques, as well as the integration of resource availability through the 3As (Anywhere, Anything, Anytime) paradigm
  • Covers central issues related to big data from the perspective of mobility and engineering
  • Includes supplementary material: sn.pub/extras

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies (LNDECT, volume 10)

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-x
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  2. Introduction to Mobile Big Data Paradigm

    1. Front Matter

      Pages 1-1
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    2. Big Data Analytics: Applications, Prospects and Challenges

      • Konstantinos Vassakis, Emmanuel Petrakis, Ioannis Kopanakis
      Pages 3-20

    3. Levering Mobile Cloud Computing for Mobile Big Data Analytics

      • Yongxin Liu, Houbing Song
      Pages 21-39

    4. Game Theoretic Approaches in Mobile Cloud Computing Systems for Big Data Applications: A Systematic Literature Review

      • Georgios Skourletopoulos, Constandinos X. Mavromoustakis, George Mastorakis, Jordi Mongay Batalla, Ciprian Dobre, John N. Sahalos et al.
      Pages 41-62

  3. Architectures, Applications and Services for Mobile Big Data

    1. Front Matter

      Pages 63-63
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    2. Evidence-Aware Mobile Cloud Architectures

      • Huber Flores, Vassilis Kostakos, Sasu Tarkoma, Pan Hui, Yong Li
      Pages 65-84

    3. Context-Awareness in Location Based Services in the Big Data Era

      • Patrizia Grifoni, Arianna D’Ulizia, Fernando Ferri
      Pages 85-127

    4. Mobile Big Data in Vehicular Networks: The Road to Internet of Vehicles

      • Ali Kamouch, Abdelaali Chaoub, Zouhair Guennoun
      Pages 129-143

  4. Data Management for Mobile Big Data

    1. Front Matter

      Pages 145-145
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    2. Mobile Distributed Complex Event Processing—Ubi Sumus? Quo Vadimus?

      • Fabrice Starks, Vera Goebel, Stein Kristiansen, Thomas Plagemann
      Pages 147-180

    3. Electromagnetic Interference and Discontinuity Effects of Interconnections on Big Data Performance of Integrated Circuits

      • Seyi Stephen Olokede, Babu Sena Paul
      Pages 181-216

    4. Evaluating Decision Analytics from Mobile Big Data using Rough Set Based Ant Colony

      • Soumya Banerjee, Youakim Badr
      Pages 217-231

    5. Energy-Aware Issues for Handling Big Data in Mobile Cloud Computing

      • Chhabi Rani Panigrahi, Rajesh Kumar Verma, Joy Lal Sarkar, Bibudhendu Pati
      Pages 233-256

  5. Industrial Practices of Mobile Big Data-Driven Models

    1. Front Matter

      Pages 257-257
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    2. Big Data—A New Technology Trend and Factors Affecting the Implementation of Big Data in Australian Industries

      • Bhavyadipsinh Jadeja, Tomayess Issa
      Pages 259-287

    3. Extending the Sana Mobile Healthcare Platform with Features Providing ECG Analysis

      • Katerina Tsampi, Spyros Panagiotakis, Elias Hatzakis, Emmanouil Lakiotakis, Georgia Atsali, Kostas Vassilakis et al.
      Pages 289-321

    4. Social Networking in Higher Education in India

      • Anil Kumar Malleshappa, Tomayess Issa
      Pages 323-347
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Keywords

About this book

This book reports on the latest advances in mobile technologies for collecting, storing and processing mobile big data in connection with wireless communications. It presents novel approaches and applications in which mobile big data is being applied from an engineering standpoint and addresses future theoretical and practical challenges related to the big data field from a mobility perspective.

Further, it provides an overview of new methodologies designed to take mobile big data to the Cloud, enable the processing of real-time streaming events on-the-move and enhance the integration of resource availability through the ‘Anywhere, Anything, Anytime’ paradigm. By providing both academia and industry researchers and professionals with a timely snapshot of emerging mobile big data-centric systems and highlighting related pitfalls, as well as potential solutions, the book fills an important gap in the literature and fosters the further development in the area of mobile technologies for exploiting mobile big data.

Reviews

“The content is very mathematical; some chapters are very much geared toward specialists, because of the amount of equations used. Overall, it is a good book on a variety of topics related to mobile big data. It will be useful for researchers in the field.” (S. Srinivasan, Computing Reviews, May 31, 2019)

Editors and Affiliations

  • Department of Computer Science, University of Nicosia, Nicosia, Cyprus

    Georgios Skourletopoulos, Constandinos X. Mavromoustakis

  • Department of Business Administration, Technological Educational Institute Crete, Agios Nikolaos, Greece

    George Mastorakis

  • Department of Computer Science and Engineering, University Politehnica of Bucharest, Bucharest, Romania

    Ciprian Dobre

  • Department of Informatics Engineering, Technological Educational Institute of Crete, Crete, Greece

    Evangelos Pallis

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