activity
20242026
most citedDigital Twin Enabled Data-Driven Approach for Traffic Efficiency and Software-Defined Vehicular Network Optimization

6 citations · 8 across the 5 of their papers we have counts for

collaborators

7 papers

cs.NI2026★ 1 cited

A benchmarking framework for PON-based fronthaul network design

Egemen Erbayat, Gustavo B. Figueiredo, Shih-Chun Lin +3

As mobile networks transition toward 5G and 6G RAN architectures, Passive Optical Networks (PONs) offer a critical solution for cost-effective fronthaul transport. However, the lac…

cs.NI2025

Intelligent Edge Resource Provisioning for Scalable Digital Twins of Autonomous Vehicles

Mohammad Sajid Shahriar, Suresh Subramaniam, Motoharu Matsuura +2

The next generation networks offers significant potential to advance Intelligent Transportation Systems (ITS), particularly through the integration of Digital Twins (DTs). However,…

cs.NI2025

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…

cs.NI2025

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…

cs.NI2024★ 6 cited

Digital Twin Enabled Data-Driven Approach for Traffic Efficiency and Software-Defined Vehicular Network Optimization

Mohammad Sajid Shahriar, Suresh Subramaniam, Motoharu Matsuura +2

In the realms of the internet of vehicles (IoV) and intelligent transportation systems (ITS), software defined vehicular networks (SDVN) and edge computing (EC) have emerged as pro…

cs.LG2024

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…

cs.NI2024★ 1 cited

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…