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20212026
most citedA Survey on Intelligent Internet of Things: Applications, Security, Privacy, and Future Directions

9 citations · 14 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Resilient Decentralized Wireless Federated Learning via Gradient Tracking with AdamW

Nguyen Van Thieu, Ti Ti Nguyen, Ons Aouedi +2

Wireless Internet-of-Things (IoT) edge networks require decentralized learning (DecL) methods that can operate reliably under both heterogeneous local data and communication-constr…

cs.LG2026

FedQoS: Federated QoS-Risk Learning for Heterogeneous Indoor-Outdoor Access Selection

Nguyen Van Thieu, Ti Ti Nguyen, Ons Aouedi +3

Reliable access selection in dynamic and heterogeneous indoor-outdoor environments is challenging because instantaneous radio measurements alone cannot capture future QoS degradati…

cs.LG2026

GAPSL: A Gradient-Aligned Parallel Split Learning over Data-Heterogeneous Edge Computing Systems

Zheng Lin, Ons Aouedi, Zihan Fang +4

The increasing complexity of neural networks poses significant challenges for democratizing federated learning (FL) on resource-constrained edge devices. Parallel split learning (P…

cs.NI2025

Towards Scalable O-RAN Resource Management: Graph-Augmented Proximal Policy Optimization

Duc-Thinh Ngo, Kandaraj Piamrat, Ons Aouedi +2

Open Radio Access Network (O-RAN) architectures enable flexible, scalable, and cost-efficient mobile networks by disaggregating and virtualizing baseband functions. However, this f…

cs.NI2024★ 9 cited

A Survey on Intelligent Internet of Things: Applications, Security, Privacy, and Future Directions

Ons Aouedi, Thai-Hoc Vu, Alessio Sacco +4

The rapid advances in the Internet of Things (IoT) have promoted a revolution in communication technology and offered various customer services. Artificial intelligence (AI) techni…

cs.LG2024

FLEXIBLE: Forecasting Cellular Traffic by Leveraging Explicit Inductive Graph-Based Learning

Duc Thinh Ngo, Kandaraj Piamrat, Ons Aouedi +2

From a telecommunication standpoint, the surge in users and services challenges next-generation networks with escalating traffic demands and limited resources. Accurate traffic pre…

cs.CR2021★ 5 cited

Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions

Shaashwat Agrawal, Sagnik Sarkar, Ons Aouedi +5

The rapid development of the Internet and smart devices trigger surge in network traffic making its infrastructure more complex and heterogeneous. The predominated usage of mobile…