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

Y Dai, D Xu, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) is a promising paradigm to enable huge amount of data
and multimedia content to be cached in proximity to vehicles. However, high mobility of …

Cost-effective app data distribution in edge computing

X Xia, F Chen, Q He, JC Grundy… - … on Parallel and …, 2020 - ieeexplore.ieee.org
Edge computing, as an extension of cloud computing, distributes computing and storage
resources from centralized cloud to distributed edge servers, to power a variety of …

Novel edge caching approach based on multi-agent deep reinforcement learning for internet of vehicles

D Zhang, W Wang, J Zhang, T Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …

Physical-layer security in space information networks: A survey

B Li, Z Fei, C Zhou, Y Zhang - IEEE Internet of things journal, 2019 - ieeexplore.ieee.org
Research and processing development on satellite communications has strongly re-
emerged in recent years. Following the prosperity of various wireless services provided by …

Video caching, analytics, and delivery at the wireless edge: A survey and future directions

B Jedari, G Premsankar, G Illahi… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Future wireless networks will provide high-bandwidth, low-latency, and ultra-reliable Internet
connectivity to meet the requirements of different applications, ranging from virtual reality to …

Joint optimization of offloading utility and privacy for edge computing enabled IoT

X Xu, C He, Z Xu, L Qi, S Wan… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
Currently, edge computing (EC), emerging as a burgeoning paradigm, is powerful in
handling real-time resource provision for Internet of Things (IoT) applications. However, due …

Multi-access Edge Computing fundamentals, services, enablers and challenges: A complete survey

B Liang, MA Gregory, S Li - Journal of Network and Computer Applications, 2022 - Elsevier
Traffic over mobile cellular networks has significantly increased over the past decade, and
with the introduction of 5G there is a growing focus on throughput capacity, reliability, and …

CREAT: Blockchain-assisted compression algorithm of federated learning for content caching in edge computing

L Cui, X Su, Z Ming, Z Chen, S Yang… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Edge computing architectures can help us quickly process the data collected by Internet of
Things (IoT) and caching files to edge nodes can speed up the response speed of IoT …

When deep reinforcement learning meets 5G-enabled vehicular networks: A distributed offloading framework for traffic big data

Z Ning, P Dong, X Wang, MS Obaidat… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
The emerging 5G-enabled vehicular networks can satisfy various requirements of vehicles
by traffic offloading. However, limited cellular spectrum and energy supplies restrict the …

Deep reinforcement learning for mobile edge caching: Review, new features, and open issues

H Zhu, Y Cao, W Wang, T Jiang, S Jin - IEEE Network, 2018 - ieeexplore.ieee.org
Mobile edge caching is a promising technique to reduce network traffic and improve the
quality of experience of mobile users. However, mobile edge caching is a challenging …