activity
20242026
collaborators

19 papers

cs.NI2026

An Intelligent eUPF for Time-Sensitive Path Selection in B5G Edge Networks

Rodrigo Moreira, Larissa Ferreira Rodrigues Moreira, Tereza Cristina Carvalho +1

In Beyond 5G (B5G) networks, intelligent, flexible traffic management is essential to meet the stringent speed and reliability requirements of new applications. This paper presents…

cs.LG2026

Evaluating Temporal and Structural Anomaly Detection Paradigms for DDoS Traffic

Yasmin Souza Lima, Rodrigo Moreira, Larissa F. Rodrigues Moreira +2

Unsupervised anomaly detection is widely used to detect Distributed Denial-of-Service (DDoS) attacks in cloud-native 5G networks, yet most studies assume a fixed traffic representa…

cs.LG2026

Asynchronous Probability Ensembling for Federated Disaster Detection

Emanuel Teixeira Martins, Rodrigo Moreira, Larissa Ferreira Rodrigues Moreira +3

Quick and accurate emergency handling in Disaster Decision Support Systems (DDSS) is often hampered by network latency and suboptimal application accuracy. While Federated Learning…

cs.NI2026

TRACE: Traceroute-based Internet Route change Analysis with Ensemble Learning

Raul Suzuki, Rodrigo Moreira, Pedro Henrique A. Damaso de Melo +2

Detecting Internet routing instability is a critical yet challenging task, particularly when relying solely on endpoint active measurements. This study introduces TRACE, a MachineL…

cs.DC2026

Data Augmentation and Convolutional Network Architecture Influence on Distributed Learning

Victor Forattini Jansen, Emanuel Teixeira Martins, Yasmin Souza Lima +3

Convolutional Neural Networks (CNNs) have proven to be highly effective in solving a broad spectrum of computer vision tasks, such as classification, identification, and segmentati…

cs.NI2026

NeuroScaler: Towards Energy-Optimal Autoscaling for Container-Based Services

Alisson O. Chaves, Rodrigo Moreira, Larissa F. Rodrigues Moreira +7

Future networks must meet stringent requirements while operating within tight energy and carbon constraints. Current autoscaling mechanisms remain workload-centric and infrastructu…