Results 181 to 190 of about 1,571,441 (262)

Distributed Deep Multi-Agent Reinforcement Learning for Cooperative Edge Caching in Internet-of-Vehicles

IEEE Transactions on Wireless Communications, 2023
Edge caching is a promising approach to reduce duplicate content transmission in Internet-of-Vehicles (IoVs). Several Reinforcement Learning (RL) based edge caching methods have been proposed to improve the resource utilization and reduce the backhaul ...
Huan Zhou, Kai Jiang, Shibo He, Geyong Min, Jie Wu   +4 more
semanticscholar   +1 more source

Novel Edge Caching Approach Based on Multi-Agent Deep Reinforcement Learning for Internet of Vehicles

IEEE transactions on intelligent transportation systems (Print), 2023
Along with the development of Internet of Vehicles (IoV) and wireless technology, the usage of applications that require low latency, such as autonomous driving and intelligent navigation, is increasing rapidly, and the demand for content is increasing ...
De-gan Zhang, W. Wang, Jie Zhang, Ting Zhang, Jinyu Du, Chun Yang   +5 more
semanticscholar   +1 more source

Federated Deep Reinforcement Learning for Recommendation-Enabled Edge Caching in Mobile Edge-Cloud Computing Networks

IEEE Journal on Selected Areas in Communications, 2023
To support rapidly increasing services and applications from users, multi-tier computing is emerged as a promising system-level computing architecture by distributing computing/caching/communication/networking capabilities between cloud servers to users,
Chuan Sun, Xiuhua Li, Junhao Wen, Xiaofei Wang, Zhu Han, Victor C. M. Leung   +5 more
semanticscholar   +1 more source

A Federated Learning-Based Edge Caching Approach for Mobile Edge Computing-Enabled Intelligent Connected Vehicles

IEEE transactions on intelligent transportation systems (Print), 2023
Massive map data transmission and the strict demand for the privacy of high-precision maps have brought significant challenges to the cache of high-precision maps in intelligent connected vehicles (ICV). Federal learning (FL) was introduced to reduce the
Chunlin Li, Yong Zhang, Youlong Luo
semanticscholar   +1 more source

Mobility-Aware Proactive Edge Caching for Large Files in the Internet of Vehicles

IEEE Internet of Things Journal, 2023
By shifting the requested content to the edge in the Internet of Vehicles (IoV), edge caching is expected to be an effective solution to satisfy the low latency and high-reliability requirements of IoV users for multimedia services.
Genghua Yu, Yixin He, Jian Wu, Zhigang Chen, Jianping Pan   +4 more
semanticscholar   +1 more source

User-Preference-Learning-Based Proactive Edge Caching for D2D-Assisted Wireless Networks

IEEE Internet of Things Journal, 2023
This work investigates proactive edge caching for device-to-device (D2D)-assisted wireless networks, where user equipment (UE) can be selected as caching nodes to assist content delivery to reduce the content transmission latency.
Dongyang Li, Haixia Zhang, Hui Ding, Tiantian Li, Daojun Liang, Dongfeng Yuan   +5 more
semanticscholar   +1 more source

AI-Assisted Edge Caching for Metaverse of Connected and Automated Vehicles: Proposal, Challenges, and Future Perspectives

IEEE Vehicular Technology Magazine, 2023
The upcoming metaverse will significantly promote the safety and efficiency of connected and automated vehicles (CAVs) as well as intelligent transportation systems (ITSs) with immersive information exchange between the parallel digital and physical ...
Bomin Mao, Yangbo Liu, Jiajia Liu, Nei Kato   +3 more
semanticscholar   +1 more source

Learning-Based Hierarchical Edge Caching for Cloud-Aided Heterogeneous Networks

IEEE Transactions on Wireless Communications, 2023
Edge caching has emerged as a promising technique against latency caused by explosive growth of mobile data traffic through caching popular contents at the edge networks.
Dongyang Li, Haixia Zhang, D. Yuan, Minggao Zhang   +3 more
semanticscholar   +1 more source

Community Detection and Attention-Weighted Federated Learning Based Proactive Edge Caching for D2D-Assisted Wireless Networks

IEEE Transactions on Wireless Communications, 2023
This work investigates proactive edge caching for D2D-assisted wireless networks, where user equipments (UEs) can be selected as caching nodes to assist content delivery. The objective of this work is to achieve a trade-off between the cost for providing
Dongyang Li, Haixia Zhang, Tiantian Li, Hui Ding, Dongfeng Yuan   +4 more
semanticscholar   +1 more source