1 citations · 1 across the 3 of their papers we have counts for
4 papers
Digital Twin-Empowered Deep Reinforcement Learning for Intelligent VNF Migration in Edge-Core Networks
Faisal Ahmed, Suresh Subramaniam, Motoharu Matsuura +2
The growing demand for services and the rapid deployment of virtualized network functions (VNFs) pose significant challenges for achieving low-latency and energy-efficient orchestr…
Federated Deep Reinforcement Learning-Driven O-RAN for Automatic Multirobot Reconfiguration
Faisal Ahmed, Myungjin Lee, Shao-Yu Lien +4
The rapid evolution of Industry 4.0 has led to the emergence of smart factories, where multirobot system autonomously operates to enhance productivity, reduce operational costs, an…
FedAuxHMTL: Federated Auxiliary Hard-Parameter Sharing Multi-Task Learning for Network Edge Traffic Classification
Faisal Ahmed, Myungjin Lee, Suresh Subramaniam +3
Federated Learning (FL) has garnered significant interest recently due to its potential as an effective solution for tackling many challenges in diverse application scenarios, for…
Prioritized Multi-Tenant Traffic Engineering for Dynamic QoS Provisioning in Autonomous SDN-OpenFlow Edge Networks
Mohammad Sajid Shahriar, Faisal Ahmed, Genshe Chen +5
This letter indicates the critical need for prioritized multi-tenant quality-of-service (QoS) management by emerging mobile edge systems, particularly for high-throughput beyond fi…