Mobile Edge Computing

Name: Mobile Edge Computing
Rating: 4 (5 reviews)

Yan Zhang

२०२१ अक्टोबर · Simula SpringerBriefs on Computing पुस्तक 9 · Springer Nature

४.०

५ समीक्षाहरू

इ-पुस्तक

113

पृष्ठहरू

रेटिङ र रिभ्यूहरूको पुष्टि गरिएको हुँदैन थप जान्नुहोस्

यो इ-पुस्तकका बारेमा

This is an open access book.
It 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.

मूल्याङ्कन र समीक्षाहरू

४.०

५ समीक्षाहरू

लेखकको बारेमा

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).

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