Resource scheduling method and device, storage medium and electronic equipment

By acquiring users' historical request information to generate tidal prediction confidence, calculating resource scheduling weights and migration performance factors, and triggering dynamic scheduling operations, the problem of insufficient tidal load prediction in cloud storage systems is solved, improving resource utilization and reducing latency fluctuations.

CN121957477APending Publication Date: 2026-05-01CHINA MOBILE INTERNET CO LTD +1
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Patent Information

Application Number
CN202511876376.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-12
Publication Date
2026-05-01

AI Technical Summary

Technical Problem

Existing cloud storage systems cannot predict load intensity and timing when facing tidal loads, resulting in low resource utilization and large fluctuations in user access latency.

Method used

By acquiring users' historical request information for cloud storage services, a tidal prediction confidence score is generated to determine whether the current business load status meets the triggering conditions of the target fluctuation scheduling cycle. The resource scheduling weight and migration performance factor of storage nodes are calculated to trigger corresponding resource scheduling operations, including cold and hot data migration, cache preheating, and Kafka message path reconstruction.

Benefits of technology

It enables forward-looking prediction of tidal load intensity and timing, improving the resource utilization of cloud storage systems and reducing the volatility of user access latency.

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Abstract

The invention discloses a resource scheduling method and device, a storage medium and electronic equipment, and relates to the technical field of cloud storage, and the method comprises the steps: firstly obtaining historical request information of a user for a cloud storage service; on the basis of historical request information, tide prediction confidence is generated; based on the tide prediction confidence, judging whether the current service load state meets a triggering condition of a target fluctuation scheduling period or not; if the current service load state meets the triggering condition of the target fluctuation scheduling period, respectively calculating a resource scheduling weight and a migration performance factor corresponding to the storage node; and triggering a corresponding resource scheduling operation based on the resource scheduling weight and the migration performance factor. Compared with the prior art, the method has the advantages that a multi-stage dynamic scheduling mechanism is constructed based on the tide prediction confidence coefficient, and accurate triggering of scheduling operations such as data migration and message queue optimization is realized in combination with the resource scheduling weight and the migration performance factor, so that the system resource utilization rate is effectively improved, and the fluctuation of user access delay is reduced.
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