Cross-domain computing task scheduling method and system based on intelligent perception

Abstract

The invention provides a cross-domain computing task scheduling method and system based on intelligent perception. The cross-domain computing task scheduling method comprises the steps of step 1, training a decision tree model based on label data; step 2, estimating and calculating the execution time of the task based on the relative time complexity; step 3, predicting a resource change trend index of each domain based on the resource historical record and an ARIMA algorithm; step 4, obtaining resource real-time state indexes of each domain by using a resource state interface; step 5, estimating migration time of the data migrated to each domain based on the available bandwidth; and step 6, deciding the task optimal execution domain based on the decision tree model and the comprehensive index. The trend prediction algorithm and the decision tree algorithm are creatively and comprehensively applied to the cross-domain computing task scheduling scene, the task resource preemption phenomenon is avoided, and the problem that the scheduling decision accuracy is low is solved; through the flow type machine learning technology, the performance problems of a trend prediction algorithm anda decision tree algorithm are solved, and the overall time of cross-domain computing task scheduling is greatly shortened.

Description

technical field [0001] The invention belongs to the field of task scheduling, in particular to a cluster-level task scheduling scenario, in particular to a computing task scheduling technology for a cross-domain computing environment. Background technique [0002] The cross-domain computing environment consists of multiple isolated domains, each domain contains one or more complete storage and computing clusters, which can independently perform specific computing tasks. The domain where the main data involved in the calculation resides is called the data domain. In a cross-domain computing environment, it is not an optimal scheduling strategy to always submit computing tasks to the data domain for execution. When the remaining resources in the data domain are insufficient, the task will enter the waiting queue, resulting in uncontrollable task start time. When the remaining resources in the data domain are tight, the computing performance of the task will be affected, resu...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problem of unbalanced resource utilization of each domain in a cross-domain computing environment, and the problem of task execution failure or excessive execution time due to insufficient resources in the domain, in order to maintain a relatively balanced resource utilization in each domain Based on the scheduling goal of shortening the overall execution time of computing tasks, a cross-domain computing task scheduling method and system based on intelligent perception is proposed to determine the optimal execution domain of specific computing tasks

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