Cloud robot resource scheduling method and system based on task classification and time sequence prediction

A time-series prediction and resource scheduling technology, applied in the field of cloud robot resource scheduling, can solve the problems of unable to find the optimal solution, less information grasped by dynamic methods, etc.

Pending Publication Date: 2021-10-29
SHANGHAI JIAO TONG UNIV +2
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Problems solved by technology

[0007] Although this kind of dynamic scheduling scheme can also solve the resource scheduling problem of cloud robots to a certain extent, compared with static methods, dynamic methods have less information, so they can only consider the optimal solutions of each part, and cannot learn from the overall situation. Looking for the best solution from a different perspective

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  • Cloud robot resource scheduling method and system based on task classification and time sequence prediction
  • Cloud robot resource scheduling method and system based on task classification and time sequence prediction

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Embodiment Construction

[0038] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0039] The embodiment of the present invention provides a cloud robot resource scheduling method based on task classification and timing prediction, which specifically includes the following steps:

[0040] Step S1: Obtain the job task sequence of the cloud robot. The task sequence needs to be completely obtained before the task starts. According to the job task requirements of the cloud robot, such as the operation ticket of the power distribution station, etc., the complete task sequence that needs to...

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Abstract

The invention provides a cloud robot resource scheduling method and system based on task classification and time sequence prediction, and relates to the technical field of cloud computing resource scheduling, and the method comprises the steps: S1, obtaining a job task sequence of a cloud robot; S2, classifying the tasks according to the dependency relationship between the cloud robot operation tasks and the cloud virtual machine; S3, obtaining an estimated value of the job duration of each job task; S4, converting cloud robot operation task scheduling into a workflow scheduling problem expressed by a directed acyclic graph (DAG); S5, simplifying the DAG generated in the step S4 according to the characteristics of the job task; and S6, solving the final DAG by using various static scheduling methods. According to the method, static analysis can be finally carried out on the operation task of the cloud robot through some preprocessing means, and a better solution for the scheduling problem can be found from the global perspective.

Description

technical field [0001] The present invention relates to the technical field of cloud computing resource scheduling, in particular to a cloud robot resource scheduling method and system based on task classification and timing prediction. Background technique [0002] The resource scheduling problem of the cloud robot aimed at by the present invention mainly considers the mapping problem between cloud job tasks and different virtual machines in the cloud. [0003] The scheduling problem of cloud computing tasks is a hot topic in the direction of cloud computing. In cloud computing tasks, by reasonably mapping a large number of cloud job tasks to a limited number of virtual machines, the earliest completion of the workflow or workload balancing can be achieved. and other service quality indicators. However, there is little research on resource scheduling methods specifically for cloud robots. The biggest difference between the resource scheduling method of cloud robots and th...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/50G06F9/455G06K9/62G06F16/901
CPCG06F9/5027G06F9/45558G06F16/9024G06F2009/4557G06F18/24
Inventor 郭梓晗韩天星王宝庄一能梁庆华吴甜张伟
Owner SHANGHAI JIAO TONG UNIV
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