The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 03, 2020

Filed:

Oct. 17, 2017
Applicant:

Tsinghua University, Beijing, CN;

Inventors:

Yuezhi Zhou, Beijing, CN;

Jinzhao Liu, Beijing, CN;

Di Zhang, Beijing, CN;

Yaoxue Zhang, Beijing, CN;

Assignee:

TSINGHUA UNIVERSITY, Beijing, CN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04L 29/08 (2006.01); G06F 11/34 (2006.01); G06F 11/20 (2006.01); H04L 12/24 (2006.01); H04L 12/26 (2006.01);
U.S. Cl.
CPC ...
H04L 67/1023 (2013.01); G06F 11/2066 (2013.01); G06F 11/3433 (2013.01); H04L 41/142 (2013.01); H04L 43/022 (2013.01); H04L 67/1008 (2013.01); G06F 11/3452 (2013.01);
Abstract

Disclosed are a method and device for detecting an abnormal load. The method includes: collecting data of each load item in all hosts; pre-processing to obtain a second sequence corresponding to each load item; obtaining a coefficient matrix and a detail vector; computing a weighted mean of abnormal load probabilities of all the coefficient vectors, to obtain an abnormal load probability of each second sequence; comparing the abnormal load probability with a confidence interval, and judging whether there is an abnormal load, and judging that there is no abnormity in the corresponding second sequence if the abnormal load probability of each second sequence is in the confidence interval; judging whether there is an abnormal load according to data of all load items and the abnormal load probability of each second sequence; and finding a bearing host that has the abnormal load from the current online service.


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