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Publications

Publications by HASLab

2025

Towards Adaptive Transactional Consistency for Georeplicated Datastores

Authors
Braga, R; Pereira, J; Coelho, F;

Publication
40TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING

Abstract
Developers of data-intensive georeplicated applications face a difficult decision when selecting a database system. As captured by the CAP theorem, CP systems such as Spanner provide strong consistency that greatly simplifies application development. AP systems such as AntidoteDB providing Transactional Causal Consistency (TCC), ensure availability in face of network partitions and isolate performance from wide-area round-trip times, but avoid lost-update anomalies only when values can be merged. Ideally, an application should be able to adapt to current data and network conditions by selecting which transactional consistency to use for each transaction. In this paper, we test the hypothesis that a georeplicated database system can be built at its core providing only TCC, hence, being AP, but allow an application to execute some transactions under Snapshot Isolation (SI), hence CP. Our main result is showing that this can be achieved even when all the interaction happens through the TCC database system, without additional communication channels between the participants. A preliminary experimental evaluation with a proof-of-concept implementation using AntidoteDB shows that this approach is feasible.

2025

CRDV: Conflict-free Replicated Data Views

Authors
Faria, N; Pereira, J;

Publication
Proc. ACM Manag. Data

Abstract
There are now multiple proposals for Conflict-free Replicated Data Types (CRDTs) in SQL databases aimed at distributed systems. Some, such as ElectricSQL, provide only relational tables as convergent replicated maps, but this omits semantics that would be useful for merging updates. Others, such as Pg\_crdt, provide access to a rich library of encapsulated column types. However, this puts merge and query processing outside the scope of the query optimizer and restricts the ability of an administrator to influence access paths with materialization and indexes. Our proposal, CRDV, overcomes this challenge by using two layers implemented as SQL views: The first provides a replicated relational table from an update history, while the second implements varied and rich types on top of the replicated table. This allows the definition of merge semantics, or even entire new data types, in SQL itself, and enables global optimization of user queries together with merge operations. Therefore, it naturally extends the scope of query optimization and local transactions to operations on replicated data, can be used to reproduce the functionality of common CRDTs with simple SQL idioms, and results in better performance than alternatives.

2025

BLADE - Byzantine-tolerant Learning under an Asynchronous and Decentralized Environment

Authors
Ferreira, G; Alonso, AN; Pereira, J;

Publication
2025 20TH EUROPEAN DEPENDABLE COMPUTING CONFERENCE COMPANION PROCEEDINGS, EDCC-C

Abstract
Machine learning models are growing, with some large language models reaching a scale of billions of trainable parameters. Training these models has since become one of the most data-hungry and computation-heavy tasks. Efforts to distribute the training task mostly follow a federated approach, where a central server oversees the training process. This approach: 1) raises concerns about data privacy; and 2) creates a single point of failure. Current proposals for a fully decentralized approach often rely on costly broadcasts to disseminate model updates and do not tolerate heterogeneity in the training data, as it makes detecting Byzantine contributions harder. We propose BLADE, a generalized fully decentralized (and asynchronous) Byzantine fault-tolerant machine learning algorithm. BLADE was designed to be configurable and adapt to harsh environments, and significantly reduces the communication overhead compared to the state of the art. We performed a comprehensive empirical evaluation, and results confirm models trained with BLADE can achieve an accuracy comparable to a centralized training instance, even if the data distribution among peers is heterogeneous, and robustly aggregate model updates in the presence of Byzantine attacks, and even against sporadic Byzantine majorities.

2025

Exploring a Quantum Programming Language with Concurrency

Authors
Jain, M; Fernandes, V; Madeira, A; Barbosa, LS;

Publication
Programming

Abstract

2025

Bridging resource theory and quantum key distribution: geometric analysis and statistical testing

Authors
D'Urbano, A; de Oliveira, M; Barbosa, LS;

Publication
QUANTUM INFORMATION PROCESSING

Abstract
Discerning between quantum and classical correlations is of great importance. Bell polytopes are well established as a fundamental tool for such a purpose. In this paper, we extend this line of inquiry by applying resource theory within the context of network scenarios, to a Quantum Key Distribution (QKD) protocol, BBM92. To achieve this, we consider the causal structure P3 to describe the protocol, and we aim to develop useful statistical tests to assess it. Our objectives are twofold: firstly, to utilise the underlying causal structure of the QKD protocol to produce a geometrical analysis of the resulting nonconvex polytope, with a focus on the classical behaviours, and secondly to devise a test within this framework to evaluate the distance between any two behaviours within the generated polytope. This approach offers a unique perspective, linking deviations from expected behaviour directly to the quality of the quantum resource involved or the residual nonclassicality in protocol execution.

2025

Hybrid quantum-classical algorithm for near-optimal planning in POMDPs

Authors
Cunha, G; Ramôa, A; Sequeira, A; Oliveira, Md; Barbosa, LS;

Publication
CoRR

Abstract

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