Big Data-Enabled Internet of Things (Computing and Networks)

ISBN 10: 1785616366 / ISBN 13: 9781785616365

Published by The Institution of Engineering and Technology, 2020

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Bibliographic Details

• Title: Big Data-Enabled Internet of Things (Computing and Networks)
• Publisher: The Institution of Engineering and Technology
• Publication Date: 2020
• Language: English
• ISBN 10: 1785616366
• ISBN 13: 9781785616365
• Binding: Hardcover
• Condition: New

About this title

Synopsis

The fields of Big Data and the Internet of Things (IoT) have seen tremendous advances, developments, and growth in recent years. The IoT is the inter-networking of connected smart devices, buildings, vehicles and other items which are embedded with electronics, software, sensors and actuators, and network connectivity that enable these objects to collect and exchange data. The IoT produces a lot of data. Big data describes very large and complex data sets that traditional data processing application software is inadequate to deal with, and the use of analytical methods to extract value from data. This edited book covers analytical techniques for handling the huge amount of data generated by the Internet of Things, from architectures and platforms to security and privacy issues, applications, and challenges as well as future directions.

About the Authors

Muhammad Usman Shahid Khan is an Assistant Professor at COMSATS University of Islamabad, Abbottabad Campus. He is an IEEE Member. His research interests include data mining, recommendation systems, computer security, and big data.

Samee U. Khan is an Associate Professor of Electrical and Computer Engineering at the North Dakota State University, Fargo, ND, USA. His research interests include optimization, robustness, and system security.

Albert Y. Zomaya is Chair Professor of High Performance Computing & Networking in the School of Computer Science, and Director of the Centre for Distributed and High-Performance Computing at the University of Sydney, Australia. His research interests span several areas in parallel and distributed computing and complex systems.