Does my BFT protocol implementation scale?

Berger, Christian; Toumia, Sadok Ben; Reiser, Hans P.

doi:10.1145/3565383.3566109

Cited by 6 publications

(2 citation statements)

References 19 publications

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“…While this is a step to make experiments more accurate, the failure model and user-generated workloads are not carried over from the real-world environment. Recent work on scalability experiments with BFT consensus protocols proposes a simulator [1]. Understanding the realism gap between simulators and real-world environments is a key part of this work.…”

Section: B the Merits Of Deploymentmentioning

confidence: 99%

“…We address this gap by presenting our deployment-first methodology for designing and evaluating decentralized systems. 1 We specifically focus on findings that can be obtained from the study of failures after the deployment. Our methodology is based on nearly two decades of experience developing the Tribler software [8], [22], [28], serving as infrastructure for deploying and evaluating decentralized mechanisms at scale.…”

Section: Introductionmentioning

confidence: 99%

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A Deployment-First Methodology to Mechanism Design and Refinement in Distributed Systems

Vos

Ishmaev

Pouwelse

et al. 2023

2023 IEEE International Conference on Pervasive Computing and Communications Workshops and Other Affiliated Events (PerCom Work

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Catalyzed by the popularity of blockchain technology, there has recently been a renewed interest in the design, implementation and evaluation of decentralized systems. Most of these systems are intended to be deployed at scale and in heterogeneous environments with real users and unpredictable workloads. Nevertheless, most research in this field evaluates such systems in controlled environments that poorly reflect the complex conditions of real-world environments. In this work, we argue that deployment is crucial to understanding decentralized mechanisms in a real-world environment and an enabler to building more robust and sustainable systems. We highlight the merits of deployment by comparing this approach with other experimental setups and show how our lab applied a deployment-first methodology. We then outline how we use Tribler, our peer-to-peer file-sharing application, to deploy and monitor decentralized mechanisms at scale. We illustrate the application of our methodology by describing a deployment trial in experimental tokenomics. Finally, we summarize four lessons learned from multiple deployment trials where we applied our methodology.

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Section: B the Merits Of Deploymentmentioning

confidence: 99%