A task scheduling method and device, electronic equipment and storage medium

By constructing an uncertainty matrix and sequence risk information, and combining entropy weight adaptive weighting, the problem of insufficient adaptability in existing task orchestration methods is solved, thereby improving the success rate and stability of task execution.

CN122431903APending Publication Date: 2026-07-21SHENZHEN SMARTCITY TECH DEV GRP CO LTD
View PDF 0 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHENZHEN SMARTCITY TECH DEV GRP CO LTD
Filing Date
2026-06-16
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing task orchestration methods rely on static configuration and lack adaptive capabilities. Heuristic scheduling is prone to getting trapped in local optima, and single-dimensional evaluation metrics cannot fully characterize the task execution status, affecting the task execution success rate.

Method used

By generating uncertainty matrices and sequence risk information for multiple candidate task execution sequences, and combining them with entropy weight adaptive weighting, the target task execution sequence is selected, thereby improving the stability and adaptability of task orchestration.

Benefits of technology

It improves the success rate of task execution, reduces the possibility of risk misjudgment, and enhances the adaptability and stability of task orchestration.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN122431903A_ABST
    Figure CN122431903A_ABST
Patent Text Reader

Abstract

Embodiments of the present application disclose a task scheduling method and device, electronic equipment and a storage medium. Embodiments of the present application obtain a plurality of sub-tasks and a plurality of association relationships between the sub-tasks; generate a plurality of candidate task execution sequences corresponding to a task target based on the plurality of sub-tasks and the plurality of association relationships; determine a plurality of uncertainty matrices corresponding to the plurality of candidate task execution sequences based on the plurality of sub-tasks and the plurality of association relationships; generate a plurality of sequence risk information corresponding to the plurality of candidate task execution sequences based on the plurality of uncertainty matrices; determine a target entropy weight corresponding to a current time period based on an initial matrix corresponding to the current time period and a historical entropy weight corresponding to a previous time period; select a target task execution sequence from the plurality of candidate task execution sequences based on the plurality of uncertainty matrices, the plurality of sequence risk information and the target entropy weight; and execute the target task execution sequence to obtain a task execution result. The scheme can improve the success rate of task execution.
Need to check novelty before this filing date? Find Prior Art