Technologies, Applications and Future Visions Ma, Xiao. creator author. aut http://id.loc.gov/vocabulary/relators/aut Xu, Mengwei. author. aut http://id.loc.gov/vocabulary/relators/aut Li, Qing. author. aut http://id.loc.gov/vocabulary/relators/aut Li, Yuanzhe. author. aut http://id.loc.gov/vocabulary/relators/aut Zhou, Ao. author. aut http://id.loc.gov/vocabulary/relators/aut Wang, Shangguang. author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text si 2024 1st ed. 2024. monographic eng

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access X, 206 p. 85 illus., 52 illus. in color. online resource. Edge computing has been identified as one of the key technologies for 5G networks and beyond due to two prominent advantages: low network latency and reduced core network load. By empowering cloud capabilities and IT service environments at the network edge, edge computing can well support applications of 5G and beyond, such as augmented/virtual reality (AR/VR), vehicular network (ultra-reliable low-latency communication services)，Internet of Things (massive machine type communication services), and mobile high-definition video (enhanced mobile broadband services). Therefore, edge computing has attracted the attention of both industry and academia since its emergence. This book highlights the progress of 5G edge computing in both industry and academia according to our long-term efforts, including the current practice of public edge providers, the research process of edge computing from academia, the integration of edge computing with 5G, and the future visions of edge computing in the 6G era. From this book, the readers can benefit from: (1) the first comprehensive measurement study on a leading public edge platform, NEP (next-generation edge platform); 2) a clear and in-depth introduction of the key technologies of 5G edge computing; (3) the latest progress of 5G-integrated edge computing; and (4) pioneering exploration of 6G edge computing based on Tiansuan constellation – an open satellite-terrestrial integrated platform. Both the researchers from academia or practitioners from industry can benefit significantly from this book. Chapter 1. Background -- Chapter 2. Recent Advancements of Public Edge Platforms -- Chapter 3. Edge Workload Prediction based on Deep Learning -- Chapter 4. Edge Computing based Computation Offloading -- Chapter 5. DynamicWorkload Scheduling in Edge Computing -- Chapter 6. Edge Service Caching -- Chapter 7. Edge Resource Provisioning -- Chapter 8. Edge Computing for 5G and 5G-based Mobile Edge Computing System -- Chapter 9. Visions of Edge Computing in 6G -- Chapter 10 Conclusions and Future Directions. by Xiao Ma, Mengwei Xu, Qing Li, Yuanzhe Li, Ao Zhou, Shangguang Wang. Mobile computing Cloud Computing Algorithms Electronic digital computers Evaluation Computational complexity Mobile Computing Cloud Computing Design and Analysis of Algorithms System Performance and Evaluation Computational Complexity QA76.59 9789819702138 https://doi.org/10.1007/978-981-97-0213-8 https://doi.org/10.1007/978-981-97-0213-8 240430 20251030112022.0 978-981-97-0213-8