Dynamic Resource Allocation-Enabled Distributed Learning as a Service for Vehicular Networks-Reference-Cited by-同舟云学术

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Dynamic Resource Allocation-Enabled Distributed Learning as a Service for Vehicular Networks

Published:2024-05-17 Issue: Volume: Page:1-4
ISSN:
Container-title:2024 Second International Conference on Data Science and Information System (ICDSIS)
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Author:

Ganesan Thirusubramanian¹,Al-Fatlawy Ramy Riad²,Srinath Suma³,Aluvala Srinivas⁴,Kumar R. Lakshmana⁵

Affiliation:

1. Cognizant Technology Solutions,Texas,USA

2. The Islamic university,College of Technical Engineering,Department of Computers Techniques Engineering,Najaf,Iraq

3. Nitte Meenakshi Institute of Technology,Department of AIML,Bengaluru,India

4. SR University,School of Computer Science and Engineering,Warangal,Telangana,India

5. Tagore Institute of Engineering & Technology,Department of Computer Science and Engineering (AI & ML),Salem,Tamil Nadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10593798/10594006/10594602.pdf?arnumber=10594602

Reference12 articles.

1. Defining Traffic States using Spatio-Temporal Traffic Graphs;Roy

2. Deep Reinforcement Learning Based Vehicle Selection for Asynchronous Federated Learning Enabled Vehicular Edge Computing

3. Contract Theory Based Incentive Mechanism for Clustered Vehicular Federated Learning

4. Towards Hierarchical Clustered Federated Learning with Model Stability on Mobile Devices

5. Computation Rate Maximization for SCMA-Aided Edge Computing in IoT Networks: A Multi-Agent Reinforcement Learning Approach

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