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Jul 2026

Energy-Optimized Federated Aggregation for Predictive Networking in Vehicular Cloud Architectures

An Energy-Optimized Federated Aggregation architecture of Predictive Networking in Vehicular Cloud Architectures (EOFA-PNVC) integrating client selection, gradient compression, and an energy-aware weighting scheme with a forecasting head that handles short-horizon state prediction of networks is suggested.

S. Narayanan, Nilesh N. Thorat, Feroz Ahmed et al. · 0 citations
Aug 2026

Communication-Aware Federated Learning for Energy Management in Edge-Cloud Autonomous Systems

The proposed framework is validated by conducting simulation-based experiments on the benchmark datasets and synthetic autonomous workloads, where the novelty lies in the design of the system-level federated learning architecture, instead of the datasets themselves.

Jyotsnarani Tripathy, D. Rajalakshmi, A. N. Ramya Shree et al. · 0 citations
Preprint Aug 2026

Hierarchical Federated Transfer Learning in Digital Twin-Based Vehicular Networks

A framework for DT-VANET is constructed, along with two algorithms designed for cloud server model updates and intra-cluster federated transfer learning, to improve the accuracy of the global model and a data quality score-based mechanism to prevent the global model from being affected by malicious vehicles is develope...

Qasim Zia, Sai-De Zhu, Haoxin Wang et al. · 0 citations
Preprint Aug 2026

Hierarchical Multi-Task Federated Learning in VANETs

An AutoEncoder-based Reliability-Optimized Hierarchical Multi-Task Federated Learning (AERO-HMTFL) framework for dynamic multi-hop clustered VANETs is proposed, which introduces a tri-weighted clustering metric that jointly considers vehicular mobility, shared-model similarity, and task affinity to produce mobility-sta...

M. S. HaghighiFard, Sinem Coleri · 0 citations
Conference Jul 2026

Online Federated Learning on Resource-Limited IoT Devices for Traffic Flow Prediction in Smart Mobility Ecosystems

Traffic congestion significantly impacts safety and urban livability in smart cities, motivating the development of accurate Traffic Flow Prediction (TFP) systems. Traditional deep learning approaches typically rely on centralized training, which is difficult to scale in distributed Internet of Things (IoT) environment...

M. Pizzolante, A. Shumba, T. Montanaro et al. · 0 citations
Open access Aug 2026

Federated Learning–Based Green AI for Sustainable Energy Optimization in 6G WSN

This study establishes a viable pathway toward integrating federated learning and green AI principles for the sustainable, intelligent operation of future 6G WSNs and introduces an adaptive client selection mechanism that prioritizes nodes with higher residual energy and better local model quality to participate in eac...

Hongyuan Wang, Shi-Kai He, Yi-Ping Jiang et al. · 0 citations

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