An on-chain governance model based on particle swarm optimization for reducing blockchain forks

Nourmohammadi, Reza et Zhang, Kaiwen. 2022. « An on-chain governance model based on particle swarm optimization for reducing blockchain forks ». IEEE Access, vol. 10. pp. 118965-118980.
Compte des citations dans Scopus : 1.

Prévisualisation

PDF Zhang-K-2022-26019.pdf - Version publiée Licence d'utilisation : Creative Commons CC BY. Télécharger (1MB) | Prévisualisation

Résumé

There is a significant drawback associated with blockchain networks in terms of their processing speed, which is one of the biggest. Due to the fact that sharding has the capability of solving this problem, the scalability of the network can be increased. One of the significant challenges in this study was determining how sharding would affect the probability of forks arising as a consequence of sharding. Towards this end, we have performed a number of experiments on the network EIP-1559 using 120 nodes in order to achieve this objective. During our analysis, we were able to determine that the number of orphan blocks on average decreases by 60% as a result of adding a shard to the system. The new on-chain governance model has also been implemented that utilizes Particle Swarm Optimization (PSO) in order to ensure that forks between different shards are reduced, as well as the probability of them occurring. The results obtained from our study give us the confidence that the proposed on-chain governance model reduces the risks associated with forking and maintains a positive user experience as a result of the results obtained.

Type de document:	Article publié dans une revue, révisé par les pairs
Professeur:	Professeur Zhang, Kaiwen
Affiliation:	Génie logiciel et des technologies de l'information
Date de dépôt:	21 déc. 2022 21:54
Dernière modification:	05 janv. 2023 20:19
URI:	https://espace2.etsmtl.ca/id/eprint/26019

Actions (Authentification requise)

Dernière vérification avant le dépôt