Deep reinforcement learning-based multi-objective edge server placement in Internet of Vehicles-Reference-Cited by-同舟云学术

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Deep reinforcement learning-based multi-objective edge server placement in Internet of Vehicles

Published:2022-04 Issue: Volume:187 Page:172-180
ISSN:0140-3664
Container-title:Computer Communications
language:en
Short-container-title:Computer Communications

Author:

Lu Jiawei^ORCID,Jiang Jielin,Balasubramanian Venki^ORCID,Khosravi Mohammad R.,Xu Xiaolong

Publisher

Elsevier BV

Subject

Computer Networks and Communications

Reference34 articles.

1. I/Q imbalance aware nonlinear wireless-powered relaying of B5G networks: Security and reliability analysis;Li;IEEE Trans. Netw. Sci. Eng.,2020

2. An optimized framework for WSN routing in the context of industry 4.0;Rani;Sensors,2021

3. Bidirectional multi-tier cognitive swarm drone 5G network;Jacob,2020

4. Traffic flow prediction based on deep learning in internet of vehicles;Chen;IEEE Trans. Intell. Transp. Syst.,2020

5. Tripres: Traffic flow prediction driven resource reservation for multimedia iov with edge computing;Xu;ACM Trans. Multimedia Comput. Commun. Appl. (TOMM),2021

Cited by 24 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Rethinking the mobile edge for vehicular services;Computer Networks;2024-11

2. RESP: A Recursive Clustering Approach for Edge Server Placement in Mobile Edge Computing;ACM Transactions on Internet Technology;2024-07-15

3. An optimization scheme for vehicular edge computing based on Lyapunov function and deep reinforcement learning;IET Communications;2024-07-02

4. VEC Collaborative Task Offloading and Resource Allocation Based on Deep Reinforcement Learning Under Parking Assistance;Wireless Personal Communications;2024-05

5. Latency-Aware Server Deployment in Internet of Vehicles Based on Multi-Agent Reinforcement Learning;2024 IEEE Wireless Communications and Networking Conference (WCNC);2024-04-21

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