Blockchain Block Data Verification Using Tree Structure Nodes
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Solution Overview
Problem
Existing blockchain technologies face inefficiencies in block data verification, particularly when new data is added, as the verification value calculation involves all data in the block, leading to increased time consumption and decreased efficiency.
Innovation Solution
A method and apparatus that select a data node for newly added data, calculate its verification value, and update the verification value of the data node based on the new data, then use this update value and original values of other data nodes to determine the block verification value, allowing for incremental calculation and improved efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all data in the block is calculated to determine the verification value, then the verification value is accurate and complete, but the calculation time increases and verification efficiency decreases
Solution Approach 1:
The patent segments the block data into multiple data nodes organized in a tree structure, where each node has its own verification value. Instead of calculating all data, only the affected data node and its parent nodes need recalculation when data changes, significantly reducing computation time while maintaining verification accuracy.
Solution Approach 2:
The patent extracts and stores verification values at each data node level in the tree structure. When verifying block data, the system extracts only the necessary verification values from relevant nodes rather than recalculating from all raw data, enabling efficient verification without sacrificing accuracy.
2Reliability
If all data in the block is calculated to determine the verification value, then data consistency is thoroughly verified, but the verification process becomes complex and time-consuming
Solution Approach 1:
The verification process is segmented into node-level operations. Each data node maintains its own verification value, and the tree structure allows verification to proceed bottom-up from leaf nodes to the root. This segmentation simplifies the overall verification process while ensuring comprehensive data consistency checking.
Solution Approach 2:
Verification values are pre-calculated and stored at each data node during data insertion or update operations. This preliminary action eliminates the need for full recalculation during verification, reducing both complexity and time requirements while maintaining reliable consistency verification.
3Measurement precision
If the verification value is calculated using all block data, then the verification is comprehensive, but the time consumption increases linearly with data amount
Solution Approach 1:
The patent divides the block data into a tree structure of data nodes, where verification can be performed on individual nodes and their ancestors rather than the entire dataset. This segmentation enables verification efficiency to remain constant or grow logarithmically with data size, while verification completeness is maintained through the hierarchical structure.
Solution Approach 2:
Different parts of the data structure have different verification requirements. The patent applies verification locally at each data node level, calculating verification values only for affected nodes and their ancestors. This local quality approach maintains verification completeness for relevant data while dramatically improving efficiency by avoiding unnecessary calculations on unaffected data.
Data Source
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AI summary
The present application discloses a method and an apparatus for verifying block data, including: selecting, from a block including a plurality of data nodes, a data node configured to store newly added data; determining a verification value of the newly added data for the data node, and calculating an update verification value of the data node based on the verification value of the newly added data; and obtaining a verification value of the block based on the update verification value of the data node and original verification values of other data nodes included in the block; where the verification value of the block is used to verify whether data stored in the block is consistent with data stored in other blocks in a blockchain. The update verification value of the data node configured to store the newly added data is determined by using the newly added data, so as to alleviate a problem in the existing technology that much time is consumed because a verification value is calculated by using all data in a block when new data is added to the block, and effectively shorten time for calculating the verification value, improving block data verification efficiency.