A data disaster recovery method supporting multi-backup path switching

By generating dynamic granular data fragments and metadata tags, a heterogeneous transmission path model is constructed. An improved Hungarian algorithm is used to allocate the optimal path and perform incremental verification, which solves the problems of blind path selection and slow recovery speed in data disaster recovery, and achieves efficient and reliable data recovery.

CN120610849BActive Publication Date: 2026-05-08ZHONGTIAN HENGHE (TIANJIN) INT TRADE CO LTD +1
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Patent Information

Application Number
CN202510709305.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-05-29
Publication Date
2026-05-08
Estimated Expiration
2045-05-29

AI Technical Summary

Technical Problem

Existing data disaster recovery methods fail to effectively consider data sensitivity, storage media characteristics, and transmission path performance, resulting in data recovery speed and reliability that cannot meet the needs of different business scenarios, and lacking a multi-backup path switching mechanism.

Method used

By generating data fragments with dynamic granularity and generating metadata tags for each fragment, a performance model of heterogeneous transmission paths is constructed. An improved Hungarian algorithm is used to allocate the optimal transmission path, and incremental integrity verification and parallel verification are performed to retransmit fragments that fail verification.

Benefits of technology

It achieves efficient adaptation of data sharding and storage media, ensuring the stability and reliability of data transmission, quickly verifying and recovering data, and meeting the recovery needs of different business scenarios.

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Abstract

The application discloses a kind of data disaster recovery methods of supporting multiple backup path switching, comprising, based on the sensitivity of input data and the generation of dynamic granularity data slice of storage medium characteristics, and generate the metadata label containing data slice identification, storage preference and recovery priority;Path quality atlas is generated for each data slice by constructing heterogeneous transmission path performance model through metadata label, and optimal transmission path is allocated, and path performance is monitored;Abnormality is detected and migrated slice by the standard deviation of cumulative transmission delay;Incremental integrity verification and Merkle proof of blockchain storage are used for parallel checking, and retransmission is preferentially checked failed slice;The application ensures the reliability and stability of data disaster recovery through the synergistic cooperation of dynamic data slicing, backup path optimization and recovery verification, to meet the real business needs.
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