Intelligent reflecting surface-aided computation offloading in UAV-enabled edge networks
Authors (first, second and last of 4)
Collection
Integration of Digital Twins and Edge Intelligence for Future Networks
5G and beyond 5G networks tend to use different emerging technologies to improve the network infrastructure, enhance government services, guarantee quality of service, and drive economic growth. In particular, the emergence and integration of digital twins (DTs) and edge intelligence is expected to show many compelling mobile applications in future networks. Edge intelligence is an emerging decentralized computing paradigm that enables artificial intelligence functionality at the network edge, which contributes to reducing response time, lowering network congestion, and enhancing privacy. A digital twin is a virtual model of a physical entity, which can enable real-time monitoring, analysis and optimization. As two promising technologies today, there is a natural advantage in the convergence of DTs and edge intelligence. The integration of DTs and edge intelligence can analyze the network data in real-time, realize the rapid response to network dynamics, thereby improving the efficiency of network management and reducing the cost of network management.
Editors
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Yueyue Dai
Huazhong University of Science and Technology, China (Emai:yueyuedai@hust.edu.cn)
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Celimuge Wu
University of Electro-Communication, Japan (Email: celimuge@uec.ac.jp)
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Ming Xiao
KTH Royal Institute of Technology, Sweden (Emai: mingx@kth.se)
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Mian Ahmad Jan
University of Sharjah, United Arab Emirates (Email: mjan@sharjah.ac.ae)
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Lei Liu
Xidian University, China (Email: leiliu@xidian.edu.cn)
