MinIndy: Automating the Deployment and Management of Hyperledger Indy Networks

The Hyperledger Indy blockchain platform, aimed at identity management networks, has gained importance, but the traditional, manual approach to network management is slow and error-prone. To reduce this, this paper presents MinIndy, a framework designed to automate the installation, configuration, and management of Indy networks without sacrificing performance. Therefore, MinIndy is a viable alternative for individuals and organizations looking to adopt Indy blockchain networks with less manual intervention. It was evaluated through the performance of its network and the results show that the network built with the framework has no loss of performance compared to one built without it.

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Publication Details

Published
2024-11-06
DOI
https://doi.org/10.1109/latincom62985.2024.10770675
Citations
6
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
2.09
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MinIndy: Automating the Deployment and Management of Hyperledger Indy Networks

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MinIndy: Automating the Deployment and Management of Hyperledger Indy Networks

Diego Abreu, Mateus Bastos, Alan Veloso, Antônio Abelém, Bruno Evaristo, Jeffson Sousa
article en
6 citations

Abstract

The Hyperledger Indy blockchain platform, aimed at identity management networks, has gained importance, but the traditional, manual approach to network management is slow and error-prone. To reduce this, this paper presents MinIndy, a framework designed to automate the installation, configuration, and management of Indy networks without sacrificing performance. Therefore, MinIndy is a viable alternative for individuals and organizations looking to adopt Indy blockchain networks with less manual intervention. It was evaluated through the performance of its network and the results show that the network built with the framework has no loss of performance compared to one built without it.

Centre for Research and Development in Telecommunications (Brazil) (BR)
Openalex Percentile: Top 12%
Distributed and Parallel Computing Systems
2.09
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