activity
20242026
collaborators

5 papers

cs.DC2026

Beyond Thread States: Diagnosing Performance Degradation with eBPF and Thread Dynamics

Diogo Landau, Jorge G. Barbosa, Nishant Saurabh

Online Data-Intensive applications face performance degradation from load variability and resource interference. While Thread State Analysis (TSA) based approaches enable identifyi…

cs.DC2025

Retrofitting Service Dependency Discovery in Distributed Systems

Diogo Landau, Gijs Blanken, Jorge Barbosa +1

Modern distributed systems rely on complex networks of interconnected services, creating direct or indirect dependencies that can propagate faults and cause cascading failures. To…

cs.LG2025

Federated learning framework for collaborative remaining useful life prognostics: an aircraft engine case study

Diogo Landau, Ingeborg de Pater, Mihaela Mitici +1

Complex systems such as aircraft engines are continuously monitored by sensors. In predictive aircraft maintenance, the collected sensor measurements are used to estimate the healt…

cs.DC2025

eBPF-Based Instrumentation for Generalisable Diagnosis of Performance Degradation

Diogo Landau, Jorge Barbosa, Nishant Saurabh

Online Data Intensive applications (e.g. message brokers, ML inference and databases) are core components of the modern internet, providing critical functionalities to connecting s…

cs.DC2024

Multi-Objective Optimization of Consumer Group Autoscaling in Message Broker Systems

Diogo Landau, Nishant Saurabh, Xavier Andrade +1

Message brokers often mediate communication between data producers and consumers by adding variable-sized messages to ordered distributed queues. Our goal is to determine the numbe…