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Backup system task scheduling method and system based on time sequence learning and prediction

A technology of backup system and time series, which is applied in the direction of multi-program device, program control design, generation of response error, etc. It can solve the problems of system resource underutilization, scheduling, too few tasks, too many tasks, etc., and achieve stable and high-efficiency business needs, meet business needs, and suppress the effects of consumption peaks and troughs

Active Publication Date: 2022-06-24
南京云信达科技有限公司
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  • Application Information

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Problems solved by technology

In this process, it is easy to cause problems such as system resource overload (insufficient scheduling leads to too many tasks) or underutilization of system resources (insufficient scheduling leads to too few tasks) and other problems.

Method used

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  • Backup system task scheduling method and system based on time sequence learning and prediction
  • Backup system task scheduling method and system based on time sequence learning and prediction
  • Backup system task scheduling method and system based on time sequence learning and prediction

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Embodiment

[0044] like figure 1 As shown, in a first aspect, an embodiment of the present invention provides a backup system task scheduling method based on time series learning and prediction, including the following steps:

[0045] S1. Obtain and perform model training according to the historical task data of task execution in the CDM backup system to construct a task time series model;

[0046] Further, obtain and record the consumption time of the task resource when performing the task in the corresponding CDM backup system according to the preset sampling interval, to obtain the task resource consumption time sequence; Obtain and record the historical execution duration of the execution task in the CDM backup system, In order to obtain the long-term sequence of task execution; model training is performed according to the task resource consumption time series and the long-term sequence of task execution to build a task time series model.

[0047] In some embodiments of the present i...

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Abstract

The invention discloses a backup system task scheduling method and system based on time sequence learning and prediction, and relates to the technical field of data center backup management. The method comprises the following steps: constructing a task time sequence model; a to-be-executed task queue is obtained and input into the task time sequence model for task prediction analysis, and a task resource consumption queue and a task execution duration queue are obtained; obtaining and carrying out task queue screening according to the current residual resource total amount of the CDM backup system, the task resource consumption queue and the task execution duration queue, and adding a target task queue which is obtained through screening and meets the execution requirement into a target execution queue; executing the task in the target execution queue, and monitoring the actual resource consumption of the task in the task execution process in real time until the task is completed. According to the invention, the task scheduling capability of the CDM backup system can be greatly improved, so that the backup system can meet business requirements more stably and efficiently.

Description

technical field [0001] The invention relates to the technical field of data center backup management, in particular, to a task scheduling method and system for a backup system based on time series learning and prediction. Background technique [0002] The task scheduling of the current mainstream backup systems is to first sort the task queues to be executed according to dimensions such as time, and then the system executes these tasks in sequence. When the system resource consumption reaches a given threshold, the subsequent task queues to be executed enter the block. Status, until the task execution is completed, the system resources are released, and the blocked task will start to be executed. In this process, it is easy to cause system resource overload (insufficient scheduling leads to too many tasks) or underutilization of system resources (insufficient scheduling leads to too few tasks). SUMMARY OF THE INVENTION [0003] In order to overcome the above problems or a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/48G06F11/14G06K9/62
CPCG06F9/4806G06F11/1446G06F18/214
Inventor 郭树岗桂巍
Owner 南京云信达科技有限公司
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