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 …
and multimedia content to be cached in proximity to vehicles. However, high mobility of …
Blockchain-based privacy-aware content caching in cognitive internet of vehicles
The Cognitive Internet of Vehicles (CIoV) introduces a cognitive engine in the traditional
Internet of Vehicles, which can realize more intelligent functions such as vehicle deployment …
Internet of Vehicles, which can realize more intelligent functions such as vehicle deployment …
Proactive content caching for internet-of-vehicles based on peer-to-peer federated learning
To cope with the increasing content requests from emerging vehicular applications, caching
contents at edge nodes is imperative to reduce service latency and network traffic on the …
contents at edge nodes is imperative to reduce service latency and network traffic on the …
Deep reinforcement learning for cooperative content caching in vehicular edge computing and networks
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 …
optimize the content placement and content delivery in the vehicular edge computing and …
Deep reinforcement learning for social-aware edge computing and caching in urban informatics
Empowered with urban informatics, transportation industry has witnessed a paradigm shift.
These developments lead to the need of content processing and sharing between vehicles …
These developments lead to the need of content processing and sharing between vehicles …
Mobility-aware proactive edge caching for connected vehicles using federated learning
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 …
technology to satisfy the increasing demands of computation-intensive and latency-sensitive …
Reputation-based blockchain for secure NDN caching in vehicular networks
Enormous research efforts have been investigated in Vehicular Ad Hoc Networking to
improve users safety, traffic condition, and provide different reliable services, that are …
improve users safety, traffic condition, and provide different reliable services, that are …
A federated learning-based edge caching approach for mobile edge computing-enabled intelligent connected vehicles
C Li, Y Zhang, Y Luo - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
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 …
have brought significant challenges to the cache of high-precision maps in intelligent …
Mobility-aware cooperative caching in vehicular edge computing based on asynchronous federated and deep reinforcement learning
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 …
users (VUs) in the roadside units (RSUs) to support real-time vehicular applications …
Deep reinforcement learning (DRL)-based device-to-device (D2D) caching with blockchain and mobile edge computing
Device-to-Device (D2D) caching assists Mobile Edge Computing (MEC) based caching in
offloading inter-domain traffic by sharing cached items with nearby users, while its …
offloading inter-domain traffic by sharing cached items with nearby users, while its …
相关搜索
- content caching permissioned blockchain
- content caching deep reinforcement
- edge computing deep reinforcement
- reinforcement learning permissioned blockchain
- caching strategy vehicular networks
- edge caching federated learning
- reinforcement learning cooperative caching
- edge caching connected vehicles
- edge computing urban informatics
- urban informatics deep reinforcement
- content caching reinforcement learning
- content caching federated learning