6G Enabled Fog Computing in IoT (eBook)

Over the past few years, the demand for data traffic has experienced explosive growth thanks to the increasing need to stay online. New applications of communications, such as wearable devices, autonomous systems, drones, and the Internet of Things (IoT), continue to emerge and generate even more data traffic with vastly different performance requirements. With the COVID-19 pandemic, the need to stay online has become even more crucial, as most of the fields, would they be industrial, educational, economic, or service-oriented, had to go online as best as they can. As the data traffic is expected to continuously strain the capacity of future communication networks, these networks need to evolve consistently in order to keep up with the growth of data traffic. Thus, more intelligent processing, operation, and optimization will be needed for tomorrow's communication networks. The Sixth Generation (6G) technology is latest approach for mobile systems or edge devices in terms of reduce traffic congestions, energy consumption blending with IoT devices applications.  The 6G network works beyond the 5G (B5G), where we can use various platforms as an application e.g. fog computing enabled IoT networks, Intelligent techniques for SDN network, 6G enabled healthcare industry, energy aware location management. Still this technology must resolve few challenges like security, IoT enabled trust network.

This book will focus on the use of AI/ML-based techniques to solve issues related to 6G enabled networks, their layers, as well as their applications. It will be a collection of original contributions regarding state-of-the-art AI/ML-based solutions for signal detection, channel modeling, resource optimization, routing protocol design, transport layer optimization, user/application behavior prediction 6G enabled software-defined networking, congestion control, communication network optimization, security, and anomaly detection. The proposed edited book emphasis on the 6G network blended with Fog-IoT networks to introduce its applications and future perspectives that helps the researcher to apply this technique in their domain and it may also helpful to resolve the challenges and future opportunities with 6G networks.

Steve Uhlig obtained a Ph.D. degree in Applied Sciences from the University of Louvain, Belgium, in 2004. From 2004 to 2006, he was a Postdoctoral Fellow of the Belgian National Fund for Scientific Research (F.N.R.S.). His thesis won the annual IBM Belgium/F.N.R.S. Computer Science Prize 2005. Between 2004 and 2006, he was a visiting scientist at Intel Research Cambridge, UK, and at the Applied Mathematics Department of University of Adelaide, Australia. Between 2006 and 2008, he was with Delft University of Technology, the Netherlands. Prior to joining Queen Mary University of London, he was a Senior Research Scientist with Technische Universität Berlin/Deutsche Telekom Laboratories, Berlin, Germany. Since January 2012, he has been the Professor of Networks and Head of the Networks Research group at Queen Mary, University of London. Between 2012 and 2016, he was a guest professor at the Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China. With expertise in network monitoring, large-scale network measurements and analysis, and network engineering, during his career he has been published in over 100 peer-reviewed journals, and awarded over £3million in grant funding. He is currently the Editor in Chief of ACM SIGCOMM Computer Communication Review, the newsletter of the ACM SIGCOMM SIG on data communications. Since December 2020, Steve has also held the position of Head of School of Electronic Engineering and Computer Science. Current Research interests: Internet measurements, software-defined networking, content delivery.