Efficient Asynchronous Federated Learning Research in the Internet of Vehicles-Reference-Cited by-同舟云学术

Efficient Asynchronous Federated Learning Research in the Internet of Vehicles

Published:2023-05-01 Issue:9 Volume:10 Page:7737-7748
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Yang Zhigang¹^ORCID,Zhang Xuhua²^ORCID,Wu Dapeng²^ORCID,Wang Ruyan²^ORCID,Zhang Puning²^ORCID,Wu Yu³^ORCID

Affiliation:

1. School of Cyber Security and Information Law, the Advanced Network and Intelligent Connection Technology Key Laboratory of Chongqing Education Commission of China, and the Chongqing Key Laboratory of Ubiquitous Sensing and Networking, Chongqing University of Posts and Telecommunications, Chongqing, China

2. School of Communication and Information Engineering, the Advanced Network and Intelligent Connection Technology Key Laboratory of Chongqing Education Commission of China, and the Chongqing Key Laboratory of Ubiquitous Sensing and Networking, Chongqing University of Posts and Telecommunications, Chongqing, China

3. School of Cyber Security and Information Law, Chongqing University of Posts and Telecommunications, Chongqing, China

Funder

National Natural Science Foundation of China

Science and Natural Science Foundation of Chongqing, China

University Innovation Research Group of Chongqing

Program for Innovation Team Building at Institutions of Higher Education in Chongqing

Youth Innovation Group Support Program of ICE Discipline of CQUPT

Science and Technology Research Program of Chongqing Municipal Education Commission

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/10106528/09993722.pdf?arnumber=9993722

Reference40 articles.

1. Communication-efficient federated learning via knowledge distillation

2. Distracted driver detection and classification;chawan;Int J Eng Res Appl,2018

3. Communication Cost Reduction with Partial Structure in Federated Learning

4. Scalable distributed DNN training using commodity GPU cloud computing

5. HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning

Cited by 10 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. Distributed Link Heterogeneity Exploitation for Attention-Weighted Robust Federated Learning in 6G Networks;IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS);2024-05-20

2. Decentralized Access Control for Privacy-Preserving Cloud-Based Personal Health Record With Verifiable Policy Update;IEEE Internet of Things Journal;2024-05-01

3. Efficient and fine-grained access control with fully-hidden policies for cloud-enabled IoT;Digital Communications and Networks;2024-05

4. FLM-ICR: a federated learning model for classification of internet of vehicle terminals using connection records;Journal of Cloud Computing;2024-03-13

5. Blockchain and signcryption enabled asynchronous federated learning framework in fog computing;Digital Communications and Networks;2024-03