4 citations · 7 across the 8 of their papers we have counts for
10 papers
Hidden in Rounds: Predicting the Time Cost of 802.11 Contention in Federated Learning
Satwat Bashir, Tasos Dagiuklas
Federated learning over IEEE~802.11 shares the wireless channel among clients that send model updates. We use ns-3 to measure the frame-delivery ratio and saturation throughput for…
FedOrbit: Adaptive Personalized Federated Learning for Non-IID LEO Satellite Constellations
Satwat Bashir, Tasos Dagiuklas, Muddesar Iqbal
Federated learning (FL) in Low Earth Orbit (LEO) satellite constellations is affected by non-IID data and irregular ground-station visibility, both driven by orbital geometry. Glob…
Fed-BAC: Federated Bandit-Guided Additive Clustering in Hierarchical Federated Learning
Satwat Bashir, Tasos Dagiuklas, Muddesar Iqbal
Hierarchical federated learning (HFL) leverages edge servers for partial aggregation in edge computing. Yet existing FL methods lack mechanisms for jointly optimizing cluster assig…
Online UAV Trajectory Planning Under QoS Constraints to Mobile Users in Urban Environments
Chenrui Qiu, Loizos Kanaris, Yongxu Zhu +1
This paper studies real-time trajectory planning and radio resource allocation for a single uncrewed aerial vehicle (UAV) serving multiple mobile ground users in an urban environme…
Agentic Trust Coordination for Federated Learning through Adaptive Thresholding and Autonomous Decision Making in Sustainable and Resilient Industrial Networks
Paul Shepherd, Tasos Dagiuklas, Bugra Alkan +1
Distributed intelligence in industrial networks increasingly integrates sensing, communication, and computation across heterogeneous and resource constrained devices. Federated lea…
Performance Comparison of IBN orchestration using LLM and SLMs
Wai Lwin Phone, Brahim El Boudani, Tasos Dagiuklas +1
The evolution of both 5G and 6G networks is driving the advancement of fully autonomous network management, placing Intent-Based Networking at the centre of this transformation. Th…
Trust Aware Federated Learning for Secure Bone Healing Stage Interpretation in e-Health
Paul Shepherd, Tasos Dagiuklas, Bugra Alkan +2
This paper presents a trust aware federated learning (FL) framework for interpreting bone healing stages using spectral features derived from frequency response data. The primary o…
Modeling UAV-aided Roadside Cell-Free Networks with Matérn Hard-Core Point Processes
Chenrui Qiu, Yongxu Zhu, Bo Tan +2
This paper investigates a uncrewed aerial vehicles (UAV)-assisted cell-free architecture for vehicular networks in road-constrained environments. Roads are modeled using a Poisson…
GreenBytes: Intelligent Energy Estimation for Edge-Cloud
Kasra Kassai, Tasos Dagiuklas, Satwat Bashir +1
This study investigates the application of advanced machine learning models, specifically Long Short-Term Memory (LSTM) networks and Gradient Booster models, for accurate energy co…
Architectural Blueprint For Heterogeneity-Resilient Federated Learning
Satwat Bashir, Tasos Dagiuklas, Kasra Kassai +1
This paper proposes a novel three tier architecture for federated learning to optimize edge computing environments. The proposed architecture addresses the challenges associated wi…