Multi-agent caching strategy for spatial-temporal popularity in iov

P He, L Cao, Y Cui, R Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Motivated by connected vehicles, the internet of vehicles (IoV) has a prosperous
development, thus a variety of IoV applications have emerged, which causes the dramatic …

Cooperative edge caching based on elastic federated and multi-agent deep reinforcement learning in next-generation networks

Q Wu, W Wang, P Fan, Q Fan, H Zhu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Edge caching is a promising solution for next-generation networks by empowering caching
units in small-cell base stations (SBSs), which allows user equipments (UEs) to fetch users' …

Deep reinforcement learning for edge caching with mobility prediction in vehicular networks

Y Choi, Y Lim - Sensors, 2023 - mdpi.com
As vehicles are connected to the Internet, various services can be provided to users.
However, if the requests of vehicle users are concentrated on the remote server, the …

Multi-Agent Reinforcement Learning-Based Joint Caching and Routing in Heterogeneous Networks

M Yang, D Gao, CH Foh, W Quan… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In this paper, we explore the problem of minimizing transmission cost among cooperative
nodes by jointly optimizing caching and routing in a hybrid network with vital support of …

Efficient content delivery in user-centric and cache-enabled vehicular edge networks with deadline-constrained heterogeneous demands

MF Pervej, R Jin, SC Lin, H Dai - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Modern connected vehicles (CVs) frequently require diverse types of content for mission-
critical decision-making and onboard users' entertainment. These contents are required to …

Efficient Vehicular Edge Computing: A Novel Approach With Asynchronous Federated and Deep Reinforcement Learning for Content Caching in VEC

W Yang, Z Liu - IEEE Access, 2024 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) technology holds great promise, but also poses significant
challenges to the limited computing power of in-vehicle devices and the capacity of …

Edge Caching Based on Deep Reinforcement Learning in Vehicular Networks

Y Choi, Y Lim - 2022 IEEE 4th Eurasia Conference on IOT …, 2022 - ieeexplore.ieee.org
As vehicles are connected to the Internet, various services such as infotainment and
automated driving can be provided. However, these services require a large amount of data …

Towards Reliable V2X Service Using UAV-Aided Coded Content Caching

M Itani - 2023 16th International Conference on Developments …, 2023 - ieeexplore.ieee.org
With the advent of intelligent transportation systems and the increase in global mobile data
traffic, the need for space-air networks to provide extra resources, service, and coverage is …

Online Monte Carlo Planning with QoS Subgoals for Data Caching in ITS MEC Networks

U Kaytaz, S Ahmadian, F Hofmann… - … Conference on Omni …, 2023 - ieeexplore.ieee.org
Multi-access Edge Computing (MEC) is an imperative for next-generation Machine-Type
Communications (MTC) to alleviate the shortcomings of Cloud Computing (CC) …

[图书][B] Collaborative Edge and On-Device Learning in Wireless Networks Under Resource Constraints

MF Pervej - 2023 - search.proquest.com
Moving resources toward the network edge is one way to appease data-hungry users in
modern wireless networks. Many real-time and mission-critical applications require …