Waste Not, Want Not: Service Migration-Assisted Federated Intelligence for Multi-Modality Mobile Edge Computing-Reference-Cited by-同舟云学术

Waste Not, Want Not: Service Migration-Assisted Federated Intelligence for Multi-Modality Mobile Edge Computing

Published:2023-10-16 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Twenty-fourth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing
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Author:

Zhou Hansong¹^ORCID,Wang Shaoying²^ORCID,Jiang Chutian²^ORCID,Zhang Xiaonan¹^ORCID,Guo Linke³^ORCID,Yuan Yukun⁴^ORCID

Affiliation:

1. Florida State University, Tallahassee, Florida, United States

2. Florida State University, Tallahassee, Florida, USA

3. Clemson University, Clemson, South Carolina, United States

4. University of Tennessee at Chattanooga, Chattanooga, Tennessee, United States

Funder

NSF (National Science Foundation)

Publisher

ACM

Reference34 articles.

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3. Ilker Bozcan and Erdal Kayacan . 2020 . AU-AIR: A Multi-modal Unmanned Aerial Vehicle Dataset for Low Altitude Traffic Surveillance. In 2020 IEEE International Conference on Robotics and Automation (ICRA). IEEE, Virtual, 8504--8510 . Ilker Bozcan and Erdal Kayacan. 2020. AU-AIR: A Multi-modal Unmanned Aerial Vehicle Dataset for Low Altitude Traffic Surveillance. In 2020 IEEE International Conference on Robotics and Automation (ICRA). IEEE, Virtual, 8504--8510.

4. nuScenes: A Multimodal Dataset for Autonomous Driving

5. Timothy Castiglia Shiqiang Wang and Stacy Patterson. 2022. Flexible Vertical Federated Learning with Heterogeneous Parties. https://arxiv.org/abs/2208.12672 Timothy Castiglia Shiqiang Wang and Stacy Patterson. 2022. Flexible Vertical Federated Learning with Heterogeneous Parties. https://arxiv.org/abs/2208.12672

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