Coalition based utility and efficiency optimization for multi-task federated learning in Internet of Vehicles-Reference-Cited by-同舟云学术

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Coalition based utility and efficiency optimization for multi-task federated learning in Internet of Vehicles

Published:2023-03 Issue: Volume:140 Page:196-208
ISSN:0167-739X
Container-title:Future Generation Computer Systems
language:en
Short-container-title:Future Generation Computer Systems

Author:

Li Zejun^ORCID,Wu Hao,Lu Yunlong

Funder

China Postdoctoral Science Foundation

Natural Science Foundation of Beijing Municipality

State Key Laboratory of Rail Traffic Control and Safety

Fundamental Research Funds for the Central Universities

Fundamental Research Funds for Central Universities of the Central South University

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference40 articles.

1. An overview of internet of vehicles;Yang;China Commun.,2014

2. Efficient privacy-preserving dual authentication and key agreement scheme for secure V2V communications in an IoV paradigm;Liu;IEEE Trans. Intell. Transp. Syst.,2017

3. Vehicular sensing networks in a smart city: Principles, technologies and applications;Wang;IEEE Wirel. Commun.,2017

4. Connected vehicles: Solutions and challenges;Lu;IEEE Internet Things J.,2014

5. Internet of vehicles in big data era;Xu;IEEE/CAA J. Autom. Sin.,2018

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1. A Heuristic Task Allocation Method Based on Overlapping Coalition Formation Game for Heterogeneous UAVs;IEEE Internet of Things Journal;2024-09-01

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5. Traffic offloading for postdisaster rescue in UAV‐assisted networks: A coalition formation game approach;Concurrency and Computation: Practice and Experience;2023-12-28

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