Mobile Edge Computing
The Simula SpringerBriefs on Computing aims to provide introductions to select areas of research in computing. Each volume aims to provide an introduction to, and overview over, research fields that can otherwise be inaccessible. This is the ninth volume in this series.
Mobile Edge Computing by Yan Zhang is now available for download. This open access book offers comprehensive, self-contained knowledge on Mobile Edge Computing (MEC), which is a very promising technology for achieving intelligence in the next-generation wireless communications and computing networks.
The book starts with the basic concepts, key techniques and network architectures of MEC. Then, we present the wide applications of MEC, including edge caching, 6G networks, Internet of Vehicles, and UAVs. In the last part, we present new opportunities when MEC meets blockchain, Artificial Intelligence, and distributed machine learning (e.g., federated learning). We also identify the emerging applications of MEC in pandemic, industrial Internet of Things and disaster management.
The book allows an easy cross-reference owing to the broad coverage on both the principle and applications of MEC. The book is written for people interested in communications and computer networks at all levels. The primary audience includes senior undergraduates, postgraduates, educators, scientists, researchers, developers, engineers, innovators and research strategists.
About the author
Yan Zhang is currently Full Professor with the Department of Informatics, University of Oslo, Norway. He received the Ph.D. degree from the School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore. He received M.S. and B.S from Beihang University and Nanjing University of Post and Telecommunications, respectively. His research interests include next-generation wireless networks leading to 5G beyond/6G, green and secure cyber-physical systems (e.g., smart grid and transport). Since 2018, Prof. Zhang was a recipient of the global "Highly Cited Researcher" Award (Web of Science top 1% most cited worldwide).