Conference Papers Year : 2022

Simulation study of Sycomore ++ , a self-adapting graph-based permissionless distributed ledger

Abstract

The arrival of Bitcoin [1] drove the shift to decentralized ecosystems through the exchange of transactions without intermediary. However, one of the main challenges that need to face permissionless blockchains are scalability and security. In this paper, we present a performance evaluation of Sycomore ++ , a permissionless graph-based distributed ledger whose main feature is to dynamically self-adapt the number of created blocks to the current number of submitted transactions, and compare them with the ones of Bitcoin and Sycomore, a graph-based distributed ledger. Our evaluation relies on agentbased simulations to evaluate the capability of these distributed ledgers to address the aforementioned challenges, within different execution contexts.
Fichier principal
Vignette du fichier
main.pdf (641.5 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-03637382 , version 1 (11-04-2022)

Identifiers

  • HAL Id : hal-03637382 , version 1

Cite

Aimen Djari, Emmanuelle Anceaume, Sara Tucci-Piergiovanni. Simulation study of Sycomore ++ , a self-adapting graph-based permissionless distributed ledger. Conference on Blockchain Research & Applications for Innovative Networks and Services (BRAINS), Sep 2022, Paris, France. ⟨hal-03637382⟩
159 View
162 Download

Share

More