A Hybrid Proactive Caching System in Vehicular Networks Based on Contextual Multi-Armed Bandit Learning
Proactive edge caching has been regarded as an effective approach to satisfy user experience in mobile networks by providing seamless content transmission and reducing network delay. This is particularly useful in rapidly changing vehicular networks. This paper addresses the proactive edge caching (...
Auteurs principaux: | Qiao Wang, David Grace |
---|---|
Format: | Article |
Langue: | English |
Publié: |
IEEE
2023-01-01
|
Collection: | IEEE Access |
Sujets: | |
Accès en ligne: | https://ieeexplore.ieee.org/document/10077392/ |
Documents similaires
-
Proactive Edge Caching in Vehicular Networks: An Online Bandit Learning Approach
par: Qiao Wang, et autres
Publié: (2022-01-01) -
Optimized Distributed Proactive Caching Based on Movement Probability of Vehicles in Content-Centric Vehicular Networks
par: Seungmin Oh, et autres
Publié: (2022-04-01) -
Mobility-Aware Proactive Edge Caching Optimization Scheme in Information-Centric IoV Networks
par: Salahadin Seid Musa, et autres
Publié: (2022-02-01) -
Design of Multi-Armed Bandit-Based Routing for in-Network Caching
par: Gen Tabei, et autres
Publié: (2023-01-01) -
Hedging using reinforcement learning: Contextual k-armed bandit versus Q-learning
par: Loris Cannelli, et autres
Publié: (2023-11-01)