Traffic prediction for diverse edge IoT data using graph network
Authors (first, second and last of 5)
Collection
AI-empowered Resource Provision and Service Scheduling in Multi-Clouds
This special issue aims to attract and disseminate high-quality research results and practical solutions from both academia and industry to advance the AI-empowered multi-clouds for IoT.
Editors
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Ying Chen
Ying Chen is currently an Associate Professor with Computer School, Beijing Information Science and Technology University, Beijing. She received the PhD degree in computer science and technology from Tsinghua University, Beijing, in 2017. She was a joint PhD student in University of Waterloo from 2015 to 2016. She is the recipient of the Best Paper Award at IEEE SmartIoT 2019, Best paper Candidate Award at IEEE ICWS 2014, 2016 Google Ph. D Fellowship Award and 2014 Google Anita Borg (Google Women Techmakers Scholars Program) Award, respectively. She serves the Technical Program Committee (TPC) member of IEEE SmartIoT, IEEE HPCC, IEEE Cloud...
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Shangguang Wang
Shangguang Wang is a Professor at the School of Computer Science and Engineering, Beijing University of Posts and Telecommunications, China. He received his Ph.D. degree at Beijing University of Posts and Telecommunications in 2011. He has published more than 150 papers in journals such as IEEE JASC, TMC, TSC, and TCC, and conferences such as IJCAI, INFOCOM, AAAI and ICWS. His research interests include service computing, mobile edge computing, cloud computing, and Satellite Computing. He is currently serving as Chair of IEEE Technical Committee on Services Computing (2022-2013), and Vice-Chair of IEEE Technical Committee on Cloud Computing .
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Geyong Min
Geyong Min is a Professor in the Department of Computer Science within the College of Engineering, Mathematics and Physical Sciences at the University of Exeter, United Kingdom. He received the PhD degree in Computing Science from the University of Glasgow, United Kingdom, in 2003. His research interests include Future Internet, Computer Networks, Wireless Communications, Information Security, Modelling and Performance Engineering. He severs/served
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Qiang Ye
Qiang Ye (qiangy@mun.ca) received the Ph.D. degree in electrical and computer engineering from the University of Waterloo, ON, Canada, in 2016. Since September 2021, he has been an Assistant Professor with the Department of Computer Science, Memorial University of Newfoundland, NL, Canada. Before joining the Memorial University, he had been with the Department of Electrical and Computer Engineering and Technology, Minnesota State University, Mankato, USA, as an Assistant Professor from September ...
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Phu Thinh Do
Phu Thinh Do received the Ph.D. degrees from the Department of Electronics and Radio Engineering, Kyung Hee University, Korea, in 2016. From 2016 to 2019, he was first a postdoctoral fellow at the Digital Communication Lab, Kyung Hee University, then at Broadband Communications Research Lab, University of Waterloo, Canada. He is now an assistant professor at the Post and Telecommunication Institute of Technology - Ho Chi Minh City Campus, Vietnam. His current research interests include intelligence networks, and retail science. He served ...
Articles (28 in this collection)
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Adaptive device sampling and deadline determination for cloud-based heterogeneous federated learning
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Stateless Q-learning algorithm for service caching in resource constrained edge environment
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AI-empowered game architecture and application for resource provision and scheduling in multi-clouds
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Data-intensive workflow scheduling strategy based on deep reinforcement learning in multi-clouds
Authors (first, second and last of 4)
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COCAM: a cooperative video edge caching and multicasting approach based on multi-agent deep reinforcement learning in multi-clouds environment
Authors (first, second and last of 6)
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Collaborative on-demand dynamic deployment via deep reinforcement learning for IoV service in multi edge clouds
Authors (first, second and last of 6)
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IoV data sharing scheme based on the hybrid architecture of blockchain and cloud-edge computing
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Task offloading optimization mechanism based on deep neural network in edge-cloud environment
Authors (first, second and last of 6)
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Blockchain-based collaborative edge computing: efficiency, incentive and trust
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Predicting the total Unified Parkinson’s Disease Rating Scale (UPDRS) based on ML techniques and cloud-based update
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Lightweight similarity checking for English literatures in mobile edge computing
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Task offloading in hybrid-decision-based multi-cloud computing network: a cooperative multi-agent deep reinforcement learning
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Reinforcement learning empowered multi-AGV offloading scheduling in edge-cloud IIoT
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A collaborative computation and dependency-aware task offloading method for vehicular edge computing: a reinforcement learning approach
Authors (first, second and last of 6)
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A service composition method using improved hybrid teaching learning optimization algorithm in cloud manufacturing
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Privacy-aware and Efficient Student Clustering for Sport Training with Hash in Cloud Environment
Authors (first, second and last of 4)
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Collaborative task offloading and resource allocation with hybrid energy supply for UAV-assisted multi-clouds
Authors (first, second and last of 5)
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A maturity model for AI-empowered cloud-native databases: from the perspective of resource management
Authors (first, second and last of 4)
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Private anomaly detection of student health conditions based on wearable sensors in mobile cloud computing
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Grid-Based coverage path planning with NFZ avoidance for UAV using parallel self-adaptive ant colony optimization algorithm in cloud IoT
Authors (first, second and last of 4)
