Streamlining decentralized ledger: enhancing historical data access in Hyperledger Fabric
Date
2024
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Abstract
This thesis presents design and implementation of Indexing Solution (IS) that aims to enhance query retrieval process in Hyperledger Fabric (HLF). In order to address limitations of HLF, we introduce new indexing algorithms: the Version-Based Index (VBI) and the Block-Based Index (BBI). We also introduce several previously unsupported query APIs: GetHistoryForVersionRange (GHFVR), GetHistoryForBlockRange (GHVBR), GetHistoryForKeyRange (GHFKR). All the work we propose is designed to integrate and work seamlessly with HLF, ensuring full backward compatibility with existing architecture. Our experiments demonstrates that proposed solution significantly outperforms original HLF regarding query execution time, reducing it from 6.621 seconds to 0.019 seconds for certain queries. While VBI and BBI introduce a space index overhead, it remains comparable to the space overhead shown in HLF. Furthermore, we adopt parallel data insertion that mitigates a slower data insertion observed in both VBI and BBI. Comparison with traditional database systems (LevelDB and MySQL) and other blockchain solution from literature (Lineage Chain and vChain+) highlights significant advantage of our IS in terms of querying capabilities, paving the way for broader application of HLF.