A survey on end-edge-cloud orchestrated network computing paradigms: Transparent computing, mobile edge computing, fog computing, and cloudlet

J Ren, D Zhang, S He, Y Zhang, T Li - ACM Computing Surveys (CSUR), 2019 - dl.acm.org
Sending data to the cloud for analysis was a prominent trend during the past decades,
driving cloud computing as a dominant computing paradigm. However, the dramatically …

Edge-computing-enabled smart cities: A comprehensive survey

LU Khan, I Yaqoob, NH Tran… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Recent years have disclosed a remarkable proliferation of compute-intensive applications in
smart cities. Such applications continuously generate enormous amounts of data which …

Blockchain empowered asynchronous federated learning for secure data sharing in internet of vehicles

Y Lu, X Huang, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In Internet of Vehicles (IoV), data sharing among vehicles for collaborative analysis can
improve the driving experience and service quality. However, the bandwidth, security and …

Vehicular edge computing and networking: A survey

L Liu, C Chen, Q Pei, S Maharjan, Y Zhang - Mobile networks and …, 2021 - Springer
As one key enabler of Intelligent Transportation System (ITS), Vehicular Ad Hoc Network
(VANET) has received remarkable interest from academia and industry. The emerging …

Deep reinforcement learning for offloading and resource allocation in vehicle edge computing and networks

Y Liu, H Yu, S Xie, Y Zhang - IEEE Transactions on Vehicular …, 2019 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) is a promising technology to extend the diverse services to
the edge of Internet of Things (IoT) system. However, the static edge server deployment may …

Mobility-aware proactive edge caching for connected vehicles using federated learning

Z Yu, J Hu, G Min, Z Zhao, W Miao… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Content Caching at the edge of vehicular networks has been considered as a promising
technology to satisfy the increasing demands of computation-intensive and latency-sensitive …

Deep reinforcement learning for cooperative content caching in vehicular edge computing and networks

G Qiao, S Leng, S Maharjan, Y Zhang… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
In this article, we propose a cooperative edge caching scheme, a new paradigm to jointly
optimize the content placement and content delivery in the vehicular edge computing and …

Mobility-aware cooperative caching in vehicular edge computing based on asynchronous federated and deep reinforcement learning

Q Wu, Y Zhao, Q Fan, P Fan, J Wang… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Vehicular edge computing (VEC) can learn and cache most popular contents for vehicular
users (VUs) in the roadside units (RSUs) to support real-time vehicular applications …

Edge content caching with deep spatiotemporal residual network for IoV in smart city

X Xu, Z Fang, J Zhang, Q He, D Yu, L Qi… - ACM Transactions on …, 2021 - dl.acm.org
Internet of Vehicles (IoV) enables numerous in-vehicle applications for smart cities, driving
increasing service demands for processing various contents (eg, videos). Generally, for …

Artificial intelligence empowered edge computing and caching for internet of vehicles

Y Dai, D Xu, S Maharjan, G Qiao… - IEEE Wireless …, 2019 - ieeexplore.ieee.org
Recent advances in edge computing and caching have significant impacts on the
developments of vehicular networks. Nevertheless, the heterogeneous requirements of on …