Latency Minimization in Heterogeneous Federated Learning through Joint Compression and Resource Allocation

Ouiame Marnissi; Hajar El Hammouti; El Houcine Bergou

doi:10.1109/vtc2024-fall63153.2024.10757524

ScienceGate Book Chapters

JOURNAL ARTICLE

Latency Minimization in Heterogeneous Federated Learning through Joint Compression and Resource Allocation

Ouiame Marnissi Hajar El Hammouti El Houcine Bergou

Year: 2024 Pages: 1-5

DOI: 10.1109/vtc2024-fall63153.2024.10757524

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Latency (audio) Resource allocation Minification Joint (building) Resource management (computing) Data compression Distributed computing Computer network Artificial intelligence World Wide Web Telecommunications Engineering

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.31

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Brain Tumor Detection and Classification

Life Sciences → Neuroscience → Neurology

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Data Compression Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Latency Minimization in Heterogeneous Federated Learning through Joint Compression and Resource Allocation

Metrics

Topics

Related Documents

Latency Minimization for UAV-Enabled Federated Learning: Trajectory Design and Resource Allocation

Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learning

Mobility-Aware Joint User Scheduling and Resource Allocation for Low Latency Federated Learning

Latency Minimization for Wireless Federated Learning with Heterogeneous Local Updates

A Federated Learning Latency Minimization Method for UAV Swarms Aided by Communication Compression and Energy Allocation