Blockchain Information Traceability via Label-Based Data Segmentation
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Solution Overview
Problem
Existing information traceability systems face challenges in efficiently locating information sources, especially in scenarios with multiple source nodes, due to large data volumes and complex data transmission paths, which hinder quick source identification and increase processing time.
Innovation Solution
A blockchain-based information traceability method that classifies and filters data using type, time, and content labels to narrow the search range, allowing for efficient identification of information sources by generating and storing single-source and multi-source path data in separate storage units and dynamically adjusting storage capacity based on data generation trends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all types of source data are filtered during information traceability without classification, then comprehensive source identification is achieved, but data volume traversed becomes relatively large
Solution Approach 1:
The patent segments the unclassified source data into two distinct categories: single-source data and multi-source data. This segmentation is achieved by classifying data based on whether it originates from a single source node or multiple source nodes. By dividing the data into these segments and storing them separately, the system can traverse only the relevant segment during traceability operations, significantly reducing the data volume that needs to be processed while maintaining complete source identification capability.
2Productivity
If data is classified and stored separately by scenario, then data traversal volume is reduced, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by performing data classification and segmentation during the data ingestion phase, before traceability operations are needed. The system automatically identifies whether incoming data is single-source or multi-source and routes it to the appropriate storage location. This preliminary classification eliminates the need for complex runtime decision-making during traceability searches, improving search efficiency while keeping the system structure manageable through automated routing logic.
3Reliability
If traceability requests traverse all stored data to locate information sources, then no source is missed, but search time increases
Solution Approach 1:
The patent implements local quality by making the data storage structure adaptive to different traceability scenarios. The system provides specialized access paths: one for single-source traceability that queries only the single-source data segment, and another for multi-source traceability that queries only the multi-source data segment. This local optimization ensures that each search operation traverses only the relevant portion of the data, maintaining complete source location capability while dramatically reducing search time by avoiding unnecessary traversal of unrelated data segments.
Data Source
AI summary
The present invention provides an information traceability method and system based on a blockchain. The method includes: receiving a traceability request, where the traceability request includes a type label, a time label, and a content label; accessing information path data pre-stored in the blockchain based on the type label to obtain target path data, where the target path data is single-source path data or multi-source path data; determining a corresponding primary data set based on the time label, where the target path data includes a plurality of primary data sets; determining a corresponding secondary data set based on the content label, where the primary data set includes at least one secondary data set; and extracting path information from the secondary data set, and obtaining at least one information source based on the path information. In the technical solution of the present invention, an information source can be quickly located based on different labels in the traceability request during information traceability, which reduces a volume of data traversed during searching for the information source, saves a time for searching for the information source, and has relatively high efficiency.