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A Fault Detection Method Based on Fusion of Long-term and Short-term Prediction

A fault detection, long-term and short-term technology, applied in the information field to achieve the effect of ensuring service quality, improving the accuracy of fault prediction, and reducing uncertainty

Active Publication Date: 2021-06-18
SHENZHEN INST OF ADVANCED TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, with the continuous expansion of the container cloud scale and the increasing types of running programs, how to ensure the security and reliability of the container cloud has become a prominent challenge

Method used

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  • A Fault Detection Method Based on Fusion of Long-term and Short-term Prediction
  • A Fault Detection Method Based on Fusion of Long-term and Short-term Prediction
  • A Fault Detection Method Based on Fusion of Long-term and Short-term Prediction

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Embodiment Construction

[0034] The following combination figure 1 A specific description is given of a long-term and short-term prediction fusion fault detection method provided by the present invention.

[0035] The present invention provides a long-term and short-term prediction fusion fault detection method, comprising the following steps:

[0036] S1: Build a statistical model of data changing over time;

[0037] First, build a statistical model of data changes over time, if only the influence of time of day is considered. let y (i,d) Denotes the observation at the i-th interval on day d in the data collection. will y (i,d) Divided into two parts: the overall mean and the average deviation from the i-th time value of the day, the overall mean is μ; the i-th error of the day from the overall mean is α i (∑ i alpha i =0). The time index t can be expressed as a function of (i,d), and the following model is established:

[0038] the y t =μ+α i (1)

[0039] Further adding a week pattern. ...

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Abstract

The invention belongs to the field of information technology, and particularly relates to a fault detection method for long-term and short-term prediction fusion. By establishing a statistical model of data changing with time; The Cove prediction model adjusts the trend of the revised statistical model, and finally uses the generalized likelihood ratio algorithm to detect the fault point, and predicts the fault alarm according to the threshold value of the situation change. The present invention not only utilizes the overall rule information of the historical data change mode, but also utilizes the change characteristic information of the current real-time data to establish a long-term and short-term fusion fault prediction model, and reduces the uncertainty of a single prediction method through fusion processing, and exerts its own advantages Superiority, so as to improve the overall fault prediction accuracy, while ensuring the reliability and service quality of the container cloud, minimize or avoid the loss caused by the fault.

Description

technical field [0001] The invention belongs to the field of information technology, and in particular relates to a fault detection method for long-term and short-term prediction fusion. Background technique [0002] Container cloud is currently a mainstream cloud computing model, which has many advantages such as fast startup speed and low resource consumption. The container cloud environment faces great reliability challenges. On the one hand, with the increase of user requests and program complexity, the program is prone to abnormality; on the other hand, the number of internal servers in the cloud system is also increasing, and at the same time, the cloud computing infrastructure generally uses relatively low-end servers or PCs. machine, there are problems with the reliability of the stand-alone machine. Therefore, the container cloud environment may often fail for some reason, and these failures will further damage the cloud environment, resulting in the need to re-ex...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L12/24H04L12/26G06F11/34
CPCG06F11/3452H04L41/06H04L41/0631H04L41/145H04L43/0823
Inventor 刘雪琳叶可江须成忠
Owner SHENZHEN INST OF ADVANCED TECH
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