Multimedia Big Data Computing for IoT Applications -

Multimedia Big Data Computing for IoT Applications

Concepts, Paradigms and Solutions
Buch | Softcover
477 Seiten
2020 | 1st ed. 2020
Springer Verlag, Singapore
978-981-13-8761-6 (ISBN)
85,59 inkl. MwSt
This book considers all aspects of managing the complexity of Multimedia Big Data Computing (MMBD) for IoT applications and develops a comprehensive taxonomy. Further, the book examines the layered architecture of MMBD computing and compares the life cycle of both big data and MMBD.
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 MMBD, such as scalability, accessibility, reliability, heterogeneity, and Quality of Service (QoS) requirements, presenting case studies to demonstrate its application. Further, the book examines the layered architecture of MMBD computing and compares the life cycle of both big data and MMBD. Written by leading experts, it also includes numerous solved examples, technical descriptions, scenarios, procedures, and algorithms. 

Sudeep Tanwar is an Associate Professor in the Computer Engineering Department at the Institute of Technology of Nirma University, Ahmedabad, India. He received his Ph.D. in 2016 from the Faculty of Engineering and Technology, Mewar University, India, with a specialization in Wireless Sensor Networks. His current interests include routing issues in WSN, integration of sensors in the cloud, computational aspects of smart grids, and assessment of fog computing in BASN. He has authored three books: Routing in Heterogeneous Wireless Sensor Networks (ISBN: 978-3-330-02892-0), Big Data Analytics (ISBN: 978-93-83992-25-8), and Mobile Computing (ISBN: 978-93-83992-25-6). He is an associate editor of the Security and Privacy Journal, and is a member of the IAENG, ISTE, and CSTA. Dr. Sudhanshu Tyagi is an Assistant Professor in the Department of Electronics and Communication Engineering, Thapar Institute of Engineering and Technology, Deemed University, India. Hereceived his Ph.D. in 2016 from the Faculty of Engineering and Technology, Mewar University, India, with a specialization in Wireless Sensor Networks; and a Master’s degree in Technology with honors in Electronics & Communication Engineering in 2005 from the National Institute of Technology, Kurukshetra, India. His research focuses on wireless sensor networks and body area sensor networks. He has co-authored two books:Big Data Analytics (ISBN: 978-93-83992-25-8), and Mobile Computing (ISBN: 978-93-83992-25-6). He is an associate editor of the Security and Privacy Journal, and is a member of the IEEE, IAENG, ISTE, and CSTA. Dr. Neeraj Kumar is currently an Associate Professor in the Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Deemed University, India. He received his Ph.D. degree in Computer Science and Engineering from Shri Mata Vaishno Devi University, India, in 2009. He was then a Postdoctoral Research Fellow at Coventry University, U.K. His research focuses on distributed systems, security and cryptography and body area networks. He is on the editorial board of the Journal of Network and Computer Applications and the International Journal of Communication Systems. He has published more than 150 research papers in leading journals and conferences in the areas of communications, security and cryptography. He is also a member of the IEEE and IEEE ComSoc.

Multimedia Big data computing for IoT .- Energy Conservation in MMBD Computing and IoT – A Challenge.- An Architecture for the Real-Time Data Stream Monitoring in IoT.- Deep learning for Multimedia data in IoT.- Random Forest based Sarcastic Tweet Classification using multiple feature Collection.- Peak Average Power Ratio reduction in FBMC using SLM & PTS techniques.- Intelligent Personality Analysis on Indicators in IoT-MMBD Enabled Environment.- Data Reduction in MMBD Computing.- Large Scale MMBD Management and Retrieval.- Data Reduction Technique for Capsule Endoscopy.- Multimedia Social Big Data: Mining.- Advertisement prediction in social media environment using big data framework.

Erscheinungsdatum
Reihe/Serie Intelligent Systems Reference Library ; 163
Zusatzinfo 121 Illustrations, color; 70 Illustrations, black and white; XIV, 477 p. 191 illus., 121 illus. in color.
Verlagsort Singapore
Sprache englisch
Maße 155 x 235 mm
Themenwelt Mathematik / Informatik Informatik Datenbanken
Informatik Netzwerke Sicherheit / Firewall
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik
Schlagworte Big Data Analytics • Cloud Computing • cognitive computing • Data Warehousing • Hadoop • Interactive Multimedia Documents • Multimedia data mining and analytics • Multimedia enabled sensors in IoT • Multimedia tools & applications
ISBN-10 981-13-8761-3 / 9811387613
ISBN-13 978-981-13-8761-6 / 9789811387616
Zustand Neuware
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