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Communication Dans Un Congrès Année : 2022

An agent-based simulation study of Sycomore ++ , a scalable and self-adapting graph-based permissionless distributed ledger

Résumé

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. One of the main lessons drawn from these intensive simulations is the capability of Sycomore ++ to drastically reduce transaction confirmation time with respect to the other two ledgers, to quickly react to any sudden variation of the transaction submission rate, to minimize the computational power waste w.r.t. PoW-based permissionless distributed ledgers, and to surpass Bitcoin in terms of resilience to a network adversarial environment. We also study resilience to adversarial miners that want to endanger the quality of the graph showing that, as in Bitcoin, the adversary is limited by its computational power.
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Dates et versions

hal-03589399 , version 1 (25-02-2022)

Identifiants

  • HAL Id : hal-03589399 , version 1

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Emmanuelle Anceaume, Aimen Djari, Sara Tucci-Piergiovanni. An agent-based simulation study of Sycomore ++ , a scalable and self-adapting graph-based permissionless distributed ledger. The 37th ACM/SIGAPP Symposium On Applied Computing (SAC), Apr 2022, Virtual, France. ⟨hal-03589399⟩
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