A storage and retrieval method and system based on spatiotemporal data density perception

By combining a loose quadtree and density-aware indexing approach with a distributed columnar database, the problem of inadequate data density and distribution in spatiotemporal data storage and retrieval is solved, achieving efficient and low-cost data management and query optimization.

CN117370347BActive Publication Date: 2026-05-29ZHONGKE (XIAMEN) DATA INTELLIGENCE RES INST
View PDF 2 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHONGKE (XIAMEN) DATA INTELLIGENCE RES INST
Filing Date
2023-10-10
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing spatiotemporal data storage and retrieval technologies fail to fully consider data density, distribution, and changes, resulting in storage structures and query strategies that are not adapted to spatiotemporal data requirements, affecting management efficiency and quality.

Method used

A data density-aware method based on loose quadtrees is adopted. By combining spatial partitioning strategy and density-aware index structure with distributed columnar database, adaptive optimization of data storage and dynamic adjustment of query strategy are achieved, which can adapt to massive, dynamic and heterogeneous spatiotemporal data scenarios.

Benefits of technology

It improves the adaptability of data storage, reduces storage costs, enhances data retrieval performance and accuracy, and improves query efficiency in big data scenarios.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN117370347B_ABST
    Figure CN117370347B_ABST
Patent Text Reader

Abstract

The application relates to the technical field of spatiotemporal trajectory big data management, and particularly discloses a storage and retrieval method and system based on spatiotemporal data density sensing. The application uses the density information of spatiotemporal trajectory data to guide data storage and retrieval, so that data management is more in line with the characteristics and requirements of spatiotemporal data. A distributed columnar database is used as a data storage platform, which has the advantages of high scalability, high availability and high performance, and is suitable for massive, dynamic and heterogeneous spatiotemporal data scenarios. By automatically identifying and dividing high-density data areas, the adaptive optimization of the data storage structure is realized, the storage space cost is saved, and the data redundancy is reduced. By designing a density-aware spatial index structure, efficient data storage and retrieval are realized, the data access speed and accuracy are improved, and by proposing a density-based query optimization strategy, the query strategy is dynamically adjusted, and the query efficiency in the big data scenario is improved.
Need to check novelty before this filing date? Find Prior Art