2D Blockchain Query Indexing With K-d-B Trees and Merkle Proofs
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Solution Overview
Problem
Current blockchain search functions are inefficient for multidimensional data searches and lack advanced analysis capabilities, leading to limited data access methods and performance issues, with existing systems also risking data manipulation and integrity breaches due to decentralized storage across nodes.
Innovation Solution
An index server and user terminal system utilizing a K-d-B tree and partial Merkle trees to index 2D location data, providing verification data for query results through hierarchical hash information, ensuring integrity and completeness of query results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If blockchain data is redundantly stored on all participating nodes, then data integrity and security are improved, but transaction performance and search efficiency deteriorate
Solution Approach 1:
The patent divides the blockchain data into two segments: original transaction data stored on all nodes for integrity, and indexed data stored centrally on an index server for efficient search. This segmentation allows nodes to maintain security while delegating search operations to a specialized component, resolving the contradiction between distributed storage reliability and search performance.
Solution Approach 2:
The patent introduces an index server as an intermediary component between users and the blockchain network. This intermediary handles all search and query operations, allowing nodes to maintain their primary function of securing transactions without being burdened by search operations, thus improving both transaction performance and search efficiency while preserving data integrity.
2Device complexity
If basic block transaction access is implemented, then system simplicity is maintained, but advanced analysis capabilities are limited
Solution Approach 1:
The patent implements a multi-functional index server that provides both basic transaction access and advanced analysis capabilities through a unified system. The index server handles diverse query types including range queries, keyword searches, and complex analytical operations, allowing the system to maintain simplicity at the node level while providing versatile analysis capabilities through the index server.
3Ease of manufacture
If 2D location data is indexed using traditional methods, then implementation simplicity is maintained, but search efficiency for multidimensional data deteriorates
Solution Approach 1:
The patent applies a K-d-B tree data structure that is specifically designed for efficiently indexing and searching multidimensional spatial data. This structure organizes 2D location data in a hierarchical manner that enables fast range queries and spatial searches, dramatically improving search efficiency for location-based data while maintaining reasonable implementation complexity through the use of established data structure algorithms.
4Productivity
If centralized indexing is implemented, then search performance is improved, but data manipulation risk increases
Solution Approach 1:
The patent implements verification data generation that provides feedback mechanisms to ensure data integrity. The index server generates verification data that allows clients to verify the authenticity of search results, creating a feedback loop that detects and prevents data manipulation while maintaining the performance benefits of centralized indexing.
Solution Approach 2:
The patent performs preliminary actions by generating verification data during the indexing process itself. This verification data is prepared in advance and stored alongside the indexed data, enabling clients to verify integrity without requiring additional computational overhead during query operations, thus maintaining high search performance while preventing data manipulation.
Data Source
AI summary
The provided index server indexes two-dimensional (2D) location data included in the transaction data as a K-d-B tree, constructs partial Merkle trees for a group of leaf nodes in the K-d-B tree, and stores hierarchical hash information based on the partial Merkle trees in each of nodes of the K-d-B tree. When a query related to the location data is acquired via the interface module, the index server searches the K-d-B tree to find a query result corresponding to the acquired query, and generates verification data for verifying the searched query result on the basis of the partial Merkle trees and the hierarchical hash information. The index server then provides the query result and the verification data to the user terminal to verify the integrity of the query result using the partial Merkle trees and the hierarchical hash information by the user terminal.