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Publications

Publications by Rui Carlos Oliveira

2013

Special track on dependable and adaptive distributed systems

Authors
Goeschka, KM; Oliveira, R; Pietzuch, P; Russello, G;

Publication
Proceedings of the ACM Symposium on Applied Computing

Abstract

2017

HTAPBench: Hybrid Transactional and Analytical Processing Benchmark

Authors
Coelho, F; Paulo, J; Vilaça, R; Pereira, JO; Oliveira, R;

Publication
Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering, ICPE 2017, L'Aquila, Italy, April 22-26, 2017

Abstract
The increasing demand for real-time analytics requires the fusion of Transactional (OLTP) and Analytical (OLAP) systems, eschewing ETL processes and introducing a plethora of proposals for the so-called Hybrid Analytical and Trans-actional Processing (HTAP) systems. Unfortunately, current benchmarking approaches are not able to comprehensively produce a unified metric from the assessment of an HTAP system. The evaluation of both engine types is done separately, leading to the use of disjoint sets of benchmarks such as TPC-C or TPC-H. In this paper we propose a new benchmark, HTAPBench, providing a unified metric for HTAP systems geared toward the execution of constantly increasing OLAP requests limited by an admissible impact on OLTP performance. To achieve this, a load balancer within HTAPBench regulates the coexistence of OLTP and OLAP workloads, proposing a method for the generation of both new data and requests, so that OLAP requests over freshly modified data are comparable across runs. We demonstrate the merit of our approach by validating it with different types of systems: OLTP, OLAP and HTAP; showing that the benchmark is able to highlight the differences between them, while producing queries with comparable complexity across experiments with negligible variability. © 2017 ACM.

2018

Proceedings of the Thirteenth EuroSys Conference, EuroSys 2018, Porto, Portugal, April 23-26, 2018

Authors
Oliveira, R; Felber, P; Hu, YC;

Publication
EuroSys

Abstract

2020

A Comparison of Message Exchange Patterns in BFT Protocols - (Experience Report)

Authors
Silva, F; Alonso, AN; Pereira, J; Oliveira, R;

Publication
Distributed Applications and Interoperable Systems - 20th IFIP WG 6.1 International Conference, DAIS 2020, Held as Part of the 15th International Federated Conference on Distributed Computing Techniques, DisCoTec 2020, Valletta, Malta, June 15-19, 2020, Proceedings

Abstract
The performance and scalability of byzantine fault-tolerant (BFT) protocols for state machine replication (SMR) have recently come under scrutiny due to their application in the consensus mechanism of blockchain implementations. This led to a proliferation of proposals that provide different trade-offs that are not easily compared as, even if these are all based on message passing, multiple design and implementation factors besides the message exchange pattern differ between each of them. In this paper we focus on the impact of different combinations of cryptographic primitives and the message exchange pattern used to collect and disseminate votes, a key aspect for performance and scalability. By measuring this aspect in isolation and in a common framework, we characterise the design space and point out research directions for adaptive protocols that provide the best trade-off for each environment and workload combination. © IFIP International Federation for Information Processing 2020.

2022

Deploying Decentralized, Privacy-Preserving Proximity Tracing

Authors
Troncoso, C; Payer, M; Hubaux, JP; Salathé, M; Larus, JR; Bugnion, E; Lueks, W; Stadler, T; Pyrgelis, A; Antonioli, D; Barman, L; Chatel, S; Paterson, KG; Capkun, S; Basin, DA; Beutel, J; Jackson, D; Roeschlin, M; Leu, P; Preneel, B; Smart, NP; Abidin, A; Gürses, SF; Veale, M; Cremers, C; Backes, M; Tippenhauer, NO; Binns, R; Cattuto, C; Barrat, A; Fiore, D; Barbosa, M; Oliveira, R; Pereira, J;

Publication
COMMUNICATIONS OF THE ACM

Abstract
[No abstract available]

2020

On the Trade-Offs of Combining Multiple Secure Processing Primitives for Data Analytics

Authors
Carvalho, H; Cruz, D; Pontes, R; Paulo, J; Oliveira, R;

Publication
Distributed Applications and Interoperable Systems - 20th IFIP WG 6.1 International Conference, DAIS 2020, Held as Part of the 15th International Federated Conference on Distributed Computing Techniques, DisCoTec 2020, Valletta, Malta, June 15-19, 2020, Proceedings

Abstract
Cloud Computing services for data analytics are increasingly being sought by companies to extract value from large quantities of information. However, processing data from individuals and companies in third-party infrastructures raises several privacy concerns. To this end, different secure analytics techniques and systems have recently emerged. These initial proposals leverage specific cryptographic primitives lacking generality and thus having their application restricted to particular application scenarios. In this work, we contribute to this thriving body of knowledge by combining two complementary approaches to process sensitive data. We present SafeSpark, a secure data analytics framework that enables the combination of different cryptographic processing techniques with hardware-based protected environments for privacy-preserving data storage and processing. SafeSpark is modular and extensible therefore adapting to data analytics applications with different performance, security and functionality requirements. We have implemented a SafeSpark’s prototype based on Spark SQL and Intel SGX hardware. It has been evaluated with the TPC-DS Benchmark under three scenarios using different cryptographic primitives and secure hardware configurations. These scenarios provide a particular set of security guarantees and yield distinct performance impact, with overheads ranging from as low as 10% to an acceptable 300% when compared to an insecure vanilla deployment of Apache Spark. © IFIP International Federation for Information Processing 2020.

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