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About

I am a researcher at HASLab and professor at the U. Minho. My research focuses on dependable distributed systems. I am interested mainly in data management, including database replication and SQL processing over NoSQL systems, and in  group communication, including consensus and gossip-based protocols for large-scale systems. I am also interested in tools for testing, evaluating, and monitoring dependable distributed systems.

Interest
Topics
Details

Details

  • Name

    José Orlando Pereira
  • Role

    Senior Researcher
  • Since

    01st November 2011
  • Nationality

    Portugal
  • Contacts

    +351253604440
    jose.o.pereira@inesctec.pt
003
Publications

2020

Black-box inter-application traffic monitoring for adaptive container placement

Authors
Neves, F; Vilaça, R; Pereira, J;

Publication
Proceedings of the 35th Annual ACM Symposium on Applied Computing

Abstract

2020

Self-tunable DBMS Replication with Reinforcement Learning

Authors
Ferreira, L; Coelho, F; Pereira, J;

Publication
Distributed Applications and Interoperable Systems - Lecture Notes in Computer Science

Abstract

2019

A Case for Dynamically Programmable Storage Background Tasks

Authors
Macedo, R; Faria, A; Paulo, J; Pereira, J;

Publication
2019 38th International Symposium on Reliable Distributed Systems Workshops (SRDSW)

Abstract

2019

Distributed Applications and Interoperable Systems

Authors
Pereira, J; Ricci, L;

Publication
Lecture Notes in Computer Science

Abstract

2018

Falcon: A Practical Log-Based Analysis Tool for Distributed Systems

Authors
Neves, F; Machado, N; Pereira, J;

Publication
48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2018, Luxembourg City, Luxembourg, June 25-28, 2018

Abstract
Programmers and support engineers typically rely on log data to narrow down the root cause of unexpected behaviors in dependable distributed systems. Unfortunately, the inherently distributed nature and complexity of such distributed executions often leads to multiple independent logs, scattered across different physical machines, with thousands or millions entries poorly correlated in terms of event causality. This renders log-based debugging a tedious, time-consuming, and potentially inconclusive task. We present Falcon, a tool aimed at making log-based analysis of distributed systems practical and effective. Falcon's modular architecture, designed as an extensible pipeline, allows it to seamlessly combine several distinct logging sources and generate a coherent space-time diagram of distributed executions. To preserve event causality, even in the presence of logs collected from independent unsynchronized machines, Falcon introduces a novel happens-before symbolic formulation and relies on an off-the-shelf constraint solver to obtain a coherent event schedule. Our case study with the popular distributed coordination service Apache Zookeeper shows that Falcon eases the log-based analysis of complex distributed protocols and is helpful in bridging the gap between protocol design and implementation. © 2018 IEEE.

Supervised
thesis

2019

Acordo Bizantino Mutável para a Blockchain

Author
Fábio Luís Baião da Silva

Institution
UM

2019

Holistic performance and scalability analysis for large scale distributed systems

Author
Francisco Nuno Teixeira Neves

Institution
UP-FCUP

2019

High Availability Architecture for Cloud Based Databases

Author
Hugo Miguel Ferreira Abreu

Institution
UM

2019

Towards a Dependable and Decentralized Software-Defined Storage Architecture

Author
Ricardo Gonçalves Macedo

Institution
UP-FCUP

2019

Adaptive consensus for the blockchain

Author
Ricardo António Gonçalves Pereira

Institution
UM