RLbR: A reinforcement learning based V2V routing framework for offloading 5G cellular IoT
Abstract 5G cellular IoT has several advantages compared to other access technologies, enabling operators to serve a wider area and more IoT devices. However, in the urban transportation system, a massive number of vehicles exhaust the available resources in the cell, resulting in excessive load in...
Main Authors: | Yaoguang Lu, Xingwei Wang, Fuliang Li, Bo Yi, Min Huang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-03-01
|
Series: | IET Communications |
Online Access: | https://doi.org/10.1049/cmu2.12346 |
Similar Items
-
Smart Architectural Framework for Symmetrical Data Offloading in IoT
by: Malvinder Singh Bali, et al.
Published: (2021-10-01) -
Deep Reinforcement Learning for Task Offloading in Edge Computing Assisted Power IoT
by: Jiangyi Hu, et al.
Published: (2021-01-01) -
Intelligent Computation Offloading Based on Digital Twin-Enabled 6G Industrial IoT
by: Jingjing Wu, et al.
Published: (2024-01-01) -
Offloading and Transmission Strategies for IoT Edge Devices and Networks
by: Jiheon Kang, et al.
Published: (2019-02-01) -
Data offloading in IoT environments: modeling, analysis, and verification
by: Ankan Ghosh, et al.
Published: (2019-03-01)