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

Aimen Djari (1) , Emmanuelle Anceaume (2) , Sara Tucci-Piergiovanni (1)

1 DILS (CEA, LIST) - Département Ingénierie Logiciels et Systèmes
2 CIDRE - Confidentialité, Intégrité, Disponibilité et Répartition

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.

Mots clés: agent-based simulation; Graph-based distributed ledger; scalability; distributed ledger quality

Domaines: Informatique [cs]

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⟩