Data center task scale prediction method based on time series data analysis

A time-series data and data center technology, which is applied in the field of data center task scale prediction based on time-series data analysis, can solve problems such as shortage and achieve good prediction results

Inactive Publication Date: 2020-08-21
周毅
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Problems solved by technology

[0004] At present, there is still a lack of construction methods for task scale prediction models based on the input data characteristics of different data centers. There is an urgent need for a set of prediction model construction methods relative to data centers, which can reasonably predict the task scale of data centers.

Method used

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  • Data center task scale prediction method based on time series data analysis
  • Data center task scale prediction method based on time series data analysis
  • Data center task scale prediction method based on time series data analysis

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Embodiment

[0044] This embodiment provides a data center task scale prediction method based on time series data analysis, which can realize the construction of a task scale prediction model for different data center input data characteristics, reasonably predict the data center task scale, and provide data center resources Reasonable scheduling, providing prediction basis for scenarios such as rapid detection and early warning of abnormal input.

[0045] the following Figure 1 to Figure 6 , specifying a data center task scale prediction method based on time series data analysis, using such as figure 1 As shown in the flow chart, its implementation method specifically includes the following steps,

[0046] T1. Collect the input data volume of the data center, including:

[0047] Collect and record the receiving information of the input node of the data center, the receiving information includes: input time point, whether the input is successful and the amount of input data, and write t...

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Abstract

The invention discloses a data center task scale prediction method based on time series data analysis, and the prediction method predicts the overall level of a data center task in a certain period oftime in the future through the collection and analysis of historical task input of a data center. The method can be applied to reasonable distribution of data center resources, data center jitter caused by frequent resource scheduling is avoided, and the overall service quality of the data center is reduced; and the method can also be applied to rapid detection and early warning of abnormal inputof the data center task scale when the deviation between the actual input quantity and the predicted value is too large.

Description

technical field [0001] The invention relates to the technical field of time series statistics and data center task scale prediction, in particular to a data center task scale prediction method based on time series data analysis. Background technique [0002] With the continuous development of big data technology, the amount of information continues to surge, and the amount of input data in the data center is also increasing. The amount of data usually determines the cost of storage and computing resources in the data center. Therefore, through the analysis and prediction of the input data scale of the data center, the storage and computing resources of the data center can be intelligently allocated and expanded, so that resources will not be surplus due to reservation. It will cause waste of energy consumption, and will not cause data center jitter due to insufficient resource allocation and continuous task allocation, resulting in a decline in data center service quality. ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/34G06N3/04G06F9/50
CPCG06F11/3442G06F11/3447G06F11/3452G06F11/3476G06F9/5061G06F2209/508G06N3/045G06N3/044
Inventor 周毅肖俊周波
Owner 周毅
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