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Conference Papers Year : 2022

QUANTAS: Quantitative User-friendly Adaptable Networked Things Abstract Simulator

Abstract

We present QUANTAS: a simulator that enables quantitative performance analysis of distributed algorithms. It has a number of attractive features. QUANTAS is an abstract simulator, therefore, the obtained results are not affected by the specifics of a particular network or operating system architecture. QUANTAS allows distributed algorithms researchers to quickly investigate a potential solution and collect data about its performance. QUANTAS programming is relatively straightforward and is accessible to theoretical researchers working in this area. To demonstrate QUANTAS capabilities, we implement and compare the behavior of two representative examples from four major classes of distributed algorithms: blockchains, distributed hash tables, consensus, and reliable data link message transmission.

Dates and versions

hal-03883308 , version 1 (03-12-2022)

Identifiers

Cite

Joseph Oglio, Kendric Hood, Mikhail Nesterenko, Sébastien Tixeuil. QUANTAS: Quantitative User-friendly Adaptable Networked Things Abstract Simulator. PODC '22: ACM Symposium on Principles of Distributed Computing, Jul 2022, Salerno, Italy. pp.40-46, ⟨10.1145/3524053.3542744⟩. ⟨hal-03883308⟩
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