Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
About
Download Photo HD

About

I am a Post Doc researcher at HASLab - High Assurance Lab. at University of Minho and INESC TEC. My research interests are distributed systems, cloud computing, large scale data management and gossip-based protocols.
I obtained a Ph.D. in Computer Science from the Universities of Minho, Aveiro and Porto (MAP-i Doctoral Program in Computer Science) in 2015 advised by Professor Rui Oliveira. My Ph.D work was focused on DataFlasks, a inherently scalable and resilient data store specifically designed for very large scale systems. Designed entirely based on unstructured gossip-based protocols, it is able to cope with very high levels of churn and faults.   I am now interested in how Dataflasks can be enriched in order to provide stronger guarantees while maintaining its scalability properties

Interest
Topics
Details

Details

  • Name

    Francisco Almeida Maia
  • Since

    01st November 2011
  • Nationality

    Portugal
  • Contacts

    +351253604440
    francisco.a.maia@inesctec.pt
004
Publications

2019

d'Artagnan: A Trusted NoSQL Database on Untrusted Clouds

Authors
Pontes, R; Maia, F; Vilaca, R; Machado, N;

Publication
2019 38th Symposium on Reliable Distributed Systems (SRDS)

Abstract

2019

Minha: Large-scale distributed systems testing made practical

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

Publication
Leibniz International Proceedings in Informatics, LIPIcs

Abstract
Testing large-scale distributed system software is still far from practical as the sheer scale needed and the inherent non-determinism make it very expensive to deploy and use realistically large environments, even with cloud computing and state-of-the-art automation. Moreover, observing global states without disturbing the system under test is itself difficult. This is particularly troubling as the gap between distributed algorithms and their implementations can easily introduce subtle bugs that are disclosed only with suitably large scale tests. We address this challenge with Minha, a framework that virtualizes multiple JVM instances in a single JVM, thus simulating a distributed environment where each host runs on a separate machine, accessing dedicated network and CPU resources. The key contributions are the ability to run off-the-shelf concurrent and distributed JVM bytecode programs while at the same time scaling up to thousands of virtual nodes; and enabling global observation within standard software testing frameworks. Our experiments with two distributed systems show the usefulness of Minha in disclosing errors, evaluating global properties, and in scaling tests orders of magnitude with the same hardware resources. © Nuno Machado, Francisco Maia, Francisco Neves, Fábio Coelho, and José Pereira; licensed under Creative Commons License CC-BY 23rd International Conference on Principles of Distributed Systems (OPODIS 2019).

2018

Proceedings of the 1st Workshop on Privacy by Design in Distributed Systems, P2DS@EuroSys 2018, Porto, Portugal, April 23, 2018

Authors
Maia, F; Mercier, H; Brito, A;

Publication
P2DS@EuroSys

Abstract

2018

Totally Ordered Replication for Massive Scale Key-Value Stores

Authors
Ribeiro, J; Machado, N; Maia, F; Matos, M;

Publication
Distributed Applications and Interoperable Systems - 18th IFIP WG 6.1 International Conference, DAIS 2018, Held as Part of the 13th International Federated Conference on Distributed Computing Techniques, DisCoTec 2018, Madrid, Spain, June 18-21, 2018, Proceedings

Abstract

2017

SafeFS: a modular architecture for secure user-space file systems: one FUSE to rule them all

Authors
Pontes, Rogerio; Burihabwa, Dorian; Maia, Francisco; Paulo, Joao; Schiavoni, Valerio; Felber, Pascal; Mercier, Hugues; Oliveira, Rui;

Publication
Proceedings of the 10th ACM International Systems and Storage Conference, SYSTOR 2017, Haifa, Israel, May 22-24, 2017

Abstract
The exponential growth of data produced, the ever faster and ubiquitous connectivity, and the collaborative processing tools lead to a clear shift of data stores from local servers to the cloud. This migration occurring across different application domains and types of users|individual or corporate|raises two immediate challenges. First, outsourcing data introduces security risks, hence protection mechanisms must be put in place to provide guarantees such as privacy, confidentiality and integrity. Second, there is no \one-size-fits-all" solution that would provide the right level of safety or performance for all applications and users, and it is therefore necessary to provide mechanisms that can be tailored to the various deployment scenarios. In this paper, we address both challenges by introducing SafeFS, a modular architecture based on software-defined storage principles featuring stackable building blocks that can be combined to construct a secure distributed file system. SafeFS allows users to specialize their data store to their specific needs by choosing the combination of blocks that provide the best safety and performance tradeoffs. The file system is implemented in user space using FUSE and can access remote data stores. The provided building blocks notably include mechanisms based on encryption, replication, and coding. We implemented SafeFS and performed indepth evaluation across a range of workloads. Results reveal that while each layer has a cost, one can build safe yet efficient storage architectures. Furthermore, the different combinations of blocks sometimes yield surprising tradeoffs. © 2017 ACM.

Supervised
thesis

2018

Aplicações web com requisitos de armazenamento e processamento privados

Author
Diogo José Linhares Couto

Institution
UM

2018

Polyglot - Sistema Poliglota de Processamento de Dados

Author
Hugo Manuel Ramos Vilas Boas Gonçalves

Institution
UM