Duo‐H: An Effectual Consensus Algorithm Using Two‐Tier Shard Consortium Blockchain Mechanism for Enhanced Privacy Protection
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Le résumé fourni par la source
ABSTRACT Blockchain is an innovative technology for storing data in decentralized, distributed, and secure chain blocks. Consortium blockchains are commonly used in transactions where transactions between organizations are also achieved by the blockchain. In the classic consortium blockchain system, entire nodes are added to each other in the process of transaction consensus. This leads to lower confidentiality in protecting transaction data within the organizations in the consortium. The throughput of the existing consortium blockchain system is still low. To solve the above problems, the paper proposes a two‐tier consortium blockchain with transaction privacy based on sharding technology. First, a trust value assessment is carried out to select the nodes of the blockchain. The duo‐head observation strategy uses these trust values to identify the nonmalicious node. Finally, the consensus separation approach based on the guarantee mechanism strategy with the shard nodes is presented. This approach is used to select reliable nodes for the blocks to be stored. The proposed consortium blockchain approach evaluation is done in terms of latency, throughput, and transactions per second metrics. As a result of the evaluations, the proposed model with 32 shards possesses 143,891 of throughput and 1.11 s of latency. Moreover, by the proposed two‐tier consortium model, time consumption is also decreased when uploading data. For a data set of 50,000, the suggested model has a time consumption of 96 s. The proposed research results in higher throughput and less latency in transactions. Also, the research enhances the scalability and reliability by overcoming the poor node issues.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Duo‐H: An Effectual Consensus Algorithm Using Two‐Tier Shard Consortium Blockchain Mechanism for Enhanced Privacy Protection
- Date Crossref
- 02/09/2024
- Éditeur
- Wiley
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Meenakshi Academy of Higher Education and Research pays non établi dans la noticeUniversité ou école supérieure
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Vinayaka Missions University pays non établi dans la noticeUniversité ou école supérieure
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St. Joseph's Institute of Technology pays non établi dans la noticeUniversité ou école supérieure
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St. Joseph’s College of Engineering Department of Computer Science and Engineering pays non établi dans la noticeUniversité ou école supérieure
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Department of Computer Science and Engineering Meenakshi College of Engineering Chennai Tamil Nadu India Department of Computer Science and Engineering pays non établi dans la noticeUniversité ou école supérieure
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Vinayaka Mission's Research Foundation Deemed to Be University Chennai Tamil Nadu India Department of Computer Science and Engineering pays non établi dans la noticeUniversité ou école supérieure
Meenakshi Academy of Higher Education and Research, Vinayaka Missions University et St. Joseph's Institute of Technology, avec 3 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.