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Sudeep Tanwar - Multimedia BigData Computing for IoT Applications

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Sudeep Tanwar Multimedia BigData Computing for IoT Applications

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Volume 163 Intelligent Systems Reference Library Series Editors Janusz - photo 1
Volume 163
Intelligent Systems Reference Library
Series Editors
Janusz Kacprzyk
Polish Academy of Sciences, Warsaw, Poland
Lakhmi C. Jain
Faculty of Engineering and Information Technology, Centre for Artificial Intelligence, University of Technology, Sydney, NSW, Australia
Faculty of Science, Technology and Mathematics, University of Canberra, Canberra, ACT, Australia
KES International, Shoreham-by-Sea, UK
Liverpool Hope University, Liverpool, UK

The aim of this series is to publish a Reference Library, including novel advances and developments in all aspects of Intelligent Systems in an easily accessible and well structured form. The series includes reference works, handbooks, compendia, textbooks, well-structured monographs, dictionaries, and encyclopedias. It contains well integrated knowledge and current information in the field of Intelligent Systems. The series covers the theory, applications, and design methods of Intelligent Systems. Virtually all disciplines such as engineering, computer science, avionics, business, e-commerce, environment, healthcare, physics and life science are included. The list of topics spans all the areas of modern intelligent systems such as: Ambient intelligence, Computational intelligence, Social intelligence, Computational neuroscience, Artificial life, Virtual society, Cognitive systems, DNA and immunity-based systems, e-Learning and teaching, Human-centred computing and Machine ethics, Intelligent control, Intelligent data analysis, Knowledge-based paradigms, Knowledge management, Intelligent agents, Intelligent decision making, Intelligent network security, Interactive entertainment, Learning paradigms, Recommender systems, Robotics and Mechatronics including human-machine teaming, Self-organizing and adaptive systems, Soft computing including Neural systems, Fuzzy systems, Evolutionary computing and the Fusion of these paradigms, Perception and Vision, Web intelligence and Multimedia.

** Indexing: The books of this series are submitted to ISI Web of Science,SCOPUS, DBLP and Springerlink.

More information about this series at http://www.springer.com/series/8578

Editors
Sudeep Tanwar , Sudhanshu Tyagi and Neeraj Kumar
Multimedia Big Data Computing for IoT Applications Concepts, Paradigms and Solutions
Editors Sudeep Tanwar Department of Computer Science and Engineering - photo 2
Editors
Sudeep Tanwar
Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India
Sudhanshu Tyagi
Department of Electronics and Communication Engineering, Thapar Institute of Engineering and Technology, Deemed University, Patiala, Punjab, India
Neeraj Kumar
Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Deemed University, Patiala, Punjab, India
ISSN 1868-4394 e-ISSN 1868-4408
Intelligent Systems Reference Library
ISBN 978-981-13-8758-6 e-ISBN 978-981-13-8759-3
https://doi.org/10.1007/978-981-13-8759-3
Springer Nature Singapore Pte Ltd. 2020
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd.

The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

With an exponential increase in the provisioning of multimedia devices over the Internet of Things (IoT), a significant amount of multimedia big data has been generated from different devices located across the globe. Current proposals in the literature mainly focus on scalar sensor data with less emphasis on the streaming multimedia big data generated from different devices. This textbook examines the unique nature and complexity of MMBD computing for IoT applications and provides unique characteristics and applications divided into different chapters for MMBD over IoT. A number of research challenges are associated with MMBD, such as scalability, accessibility, reliability, heterogeneity, and quality-of-service (QoS) requirements. This textbook is the first-ever how-to guide addressing one of the most overlooked practical, methodological, and moral questions in any nations journeys to handle the massive amount of multimedia big data being generated from IoT devices interactions: For example, how to handle the complexity of facilitating MMBD over IoT? How to organize the unstructured and heterogeneous data? How to deal with cognition and understand complexity associated with MMBD? How to address the real-time and quality-of-service requirements for MMBD applications? How to ensure scalability and computing efficiency.

The book is organized into four parts. Part I is focused on technological development, which includes five chapters. Part II discussed the multimedia big data analytics, which has five chapters. Part III illustrates the societal impact of multimedia big data with well-structured four chapters. Finally, Part IV highlights the application environments for multimedia big data analytics with four chapters.

Part I Technological Developments

Chapter presents an introduction to the multimedia big data computing for IoT applications. This chapter addresses the gap between multimedia big data challenges in IoT and multimedia big data solutions by offering the present multimedia big data framework, their advantages and limitations of the existing techniques, and the potential applications in IoT. It also presents a comprehensive overview of the multimedia big data computing for IoT applications, fundamental challenges, and research openings for multimedia big data era.

Chapter highlights various ways to achieve energy conservation in the MMBD IoT environment. The authors have focused on the investigation of the existing technologies and mechanisms in the above domains. The authors have first presented the need for energy conservation briefly and then discuss the key points of the existing solutions for saving energy in IoT communications. At the end of the paper, the authors have summarized the findings to describe the advantages and limitations of the existing mechanisms and provide insights into possible research directions.

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