4.6 Article

Sidechain: storage land registry data using blockchain improve performance of search records

Publisher

SPRINGER
DOI: 10.1007/s10586-022-03535-0

Keywords

Sidechain; Mainchain; Peer-to-peer; Blockchain; Property transaction system; Two-way peg protocol

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This article proposes a novel sidechain structure for land/property registry management framework, utilizing blockchain technology to enhance information management, decrease authentication time, and storage consumption. By using mainchain and sidechain, the proposed framework efficiently stores and searches land registry data. It outperforms existing approaches in terms of efficiency.
This article proposes a novel sidechain structure for a land/property registry management framework to overcome the limitations of an existing land registry process. This research proposes two different types of blockchains namely mainchain and sidechain. Metadata is stored in the mainchain that is publicly accessible, and non-transactional data, such as pictures, contracts, PDF, other allied information, is stored in the sidechain. It mainly focuses on using blockchain in the land registry data storage, improving information management, reducing authentication time, decreasing storage consumption that leads to optimized searching of land records in the blockchain. The proposed framework uses a summary file and InterPlanetary File System based on a Peer-to-Peer swarm-based network. The summary file concept is used for searching documents in the sidechain, which can be queried using attributes of the registry and can be accessed by only authorized parties or persons involved in that transaction. The comparative assessment establishes that the proposed approach is more efficient than the existing leading approaches. The land record search time of the proposed algorithm is on an average lesser by 60% as compared with the linear search approach and by 25% when compared with the hash table-based search algorithm. Also the proposed approach LRSA has reduces block approval time during consensus process by 55.63%, 28.24%, 25.30%, and 3.62% while comparing it with the existing leading algorithms PoW, PoS, DPoS, TrVCA, and LRSA respectively.

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