Multimedia Big Data Computing for IoT Applications Concepts, Paradig
This book considers all aspects of managing the complexity of Multimedia Big Data Computing (MMBD) for IoT applications and develops a comprehensive taxonomy. It also discusses a process model that addresses a number of research challenges associated with
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Sudeep Tanwar Sudhanshu Tyagi Neeraj Kumar Editors
Multimedia Big Data Computing for IoT Applications Concepts, Paradigms and Solutions
Intelligent Systems Reference Library Volume 163
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
Sudeep Tanwar Sudhanshu Tyagi Neeraj Kumar •
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Editors
Multimedia Big Data Computing for IoT Applications Concepts, Paradigms and Solutions
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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 ISSN 1868-4408 (electronic) Intelligent Systems Reference Library ISBN 978-981-13-8758-6 ISBN 978-981-13-8759-3 (eBook) https://doi.org/10.1007/978-981-13-8759-3 © Spr
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