PISTIS

An Event-Triggered Real-time Byzantine Resilient Protocol Suite

Journal Article (2021)
Author(s)

David Kozhaya (ABB Corporate Research Center (Switzerland))

Jérémie Decouchant (TU Delft - Data-Intensive Systems)

Vincent Rahli (University of Birmingham)

Paulo Esteves-Veríssimo (King Abdullah University of Science and Technology)

Research Group
Data-Intensive Systems
Copyright
© 2021 David Kozhaya, Jérémie Decouchant, Vincent Rahli, Paulo Esteves-Verissimo
DOI related publication
https://doi.org/10.1109/TPDS.2021.3056718
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 David Kozhaya, Jérémie Decouchant, Vincent Rahli, Paulo Esteves-Verissimo
Research Group
Data-Intensive Systems
Issue number
9
Volume number
32
Pages (from-to)
2277-2290
Reuse Rights

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Abstract

The accelerated digitalisation of society along with technological evolution have extended the geographical span of cyber-physical systems. Two main threats have made the reliable and real-time control of these systems challenging: (i) uncertainty in the communication infrastructure induced by scale, and heterogeneity of the environment and devices; and (ii) targeted attacks maliciously worsening the impact of the above-mentioned communication uncertainties, disrupting the correctness of real-time applications. This article addresses those challenges by showing how to build distributed protocols that provide both real-time with practical performance, and scalability in the presence of network faults and attacks, in probabilistic synchronous environments. We provide a suite of real-time Byzantine protocols, which we prove correct, starting from a reliable broadcast protocol, called PISTIS, up to atomic broadcast and consensus. This suite simplifies the construction of powerful distributed and decentralized monitoring and control applications, including state-machine replication. Extensive empirical simulations showcase PISTIS's robustness, latency, and scalability. For example, PISTIS can withstand message loss (and delay) rates up to 50 percent in systems with 49 nodes and provides bounded delivery latencies in the order of a few milliseconds.

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