Efficient trusted data traceability method based on segmented merkle mountain range

Key Points

• The study aims to enhance data traceability methods in blockchain by addressing concurrency and validation efficiency issues.
• Proposed a dual-layer index structure using local balanced subtrees and global Merkle mountain range.
• Utilized InterPlanetary File System (IPFS) to store raw traceability data.
• Segmented data construction based on threshold values for optimized insertion and verification.
• Demonstrated significantly improved batch insertion efficiency over traditional Merkle mountain range.
• Showed reduced integrity verification delays with concentrated data distribution.
• Exhibited higher traceability efficiency in large-scale data scenarios.

Abstract