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Load prediction method for cloud computation cluster tasks based on cluster characteristic extraction

A feature extraction and load prediction technology, applied in the field of cloud computing cluster task load prediction, can solve the problems of low execution efficiency and prediction accuracy, and large workload, and achieve the effect of accurate load trend, accurate prediction ability, and accurate prediction

Inactive Publication Date: 2018-08-17
CHANGZHOU COLLEGE OF INFORMATION TECH
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Problems solved by technology

[0030] In view of the above situation, in order to solve the problems of heavy workload, low execution efficiency and low prediction accuracy of the above-mentioned technologies, the present invention proposes a cloud computing cluster task load prediction method based on clustering feature extraction to improve cloud computing server resources. Scheduling accuracy, and reduce the waste of cloud computing service resources

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  • Load prediction method for cloud computation cluster tasks based on cluster characteristic extraction
  • Load prediction method for cloud computation cluster tasks based on cluster characteristic extraction
  • Load prediction method for cloud computation cluster tasks based on cluster characteristic extraction

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Embodiment Construction

[0078] The present invention will be further described in detail below with reference to the embodiments given in the accompanying drawings. The described embodiments include various specific details to aid in understanding, but they are to be regarded only as exemplary, some, not all, embodiments of the invention. Unless otherwise defined, the technical terms or scientific terms used herein shall have the usual meanings understood by those skilled in the art to which the present invention belongs. Meanwhile, in order to make the description more clear and concise, detailed descriptions of functions, structures and methods well known in the art will be omitted.

[0079] see figure 1 The application system architecture of the cloud computing cluster task load prediction method based on clustering feature extraction is shown. The bottom layer of the cloud cluster environment is composed of many physical machines. The physical layer provides the real CPU, memory, hard disk and ...

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Abstract

The invention relates to a load prediction method for cloud computation cluster tasks based on cluster characteristic extraction. The method comprises the following steps that historical load data ofa cloud cluster data server is called and analyzed, similar historical load curves are clustered into a type through a clustering algorithm, and accordingly K historical load curve clusters are formed; the K historical load curve clusters are analyzed; initial load data of tasks submitted by a user within certain time is collected, and the historical load curve cluster with the shortest DTW distance is selected as a cluster which the initial load data belongs to; the historical load curves closest to the initial load data are selected from the clusters which the initial load data belongs to and used as the basis of load prediction; through the load data, closest to the initial load data, of the historical load curves at a time interval, the load of the tasks submitted by the user is predicted in a future time interval. The accuracy of resource scheduling of a cloud computation server side is improved, and the waste of service resources of cloud computation is lowered.

Description

technical field [0001] The invention relates to a cloud computing cluster task load prediction method based on clustering feature extraction. Background technique [0002] Cloud computing clusters provide dynamic and easily scalable virtualized resources through the network, and reorganize, allocate, and schedule hardware and physical resources to form a configurable shared pool of virtual computing resources (resources include networks, servers, storage, application software, and services). This provides users with available, convenient, and on-demand network access, reduces user management work, and shifts the focus of user work to the business level. In recent years, many users have transferred free server applications to public cloud services. The fields of user applications are different, and the requirements for cloud computing performance and other aspects are also different. [0003] According to the different needs of users, the contract SLA (Service-Level Agreemen...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/50
CPCG06F9/5083G06F9/505
Inventor 余永佳
Owner CHANGZHOU COLLEGE OF INFORMATION TECH
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