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Detection of abnormal resource usage in a data center

A resource and data technology, applied in the field of detecting abnormal resource usage in the data center, can solve the problem of high cost

Active Publication Date: 2018-01-26
MICROSOFT TECH LICENSING LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The cost of purchasing and maintaining such excess capacity can be high

Method used

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  • Detection of abnormal resource usage in a data center
  • Detection of abnormal resource usage in a data center
  • Detection of abnormal resource usage in a data center

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Experimental program
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Embodiment Construction

[0015] In some embodiments, an abnormal activity detection ("AAD") system detects when resource usage at a data center is so high that the resource usage may be fraudulent. Such fraudulent use may be referred to as a "spoof storm" at the data center because significant fraudulent use occurs suddenly. The AAD system detects spoofing storms using a classifier for classifying whether current resource usage indicates abnormal activity resulting in abnormal resource usage at the data center. To generate classifiers, the AAD system can generate predictive models for various resources to predict normal resource usage given past resource usage. The AAD system uses resources that may increase during a spoof storm, such as number of cores in use, number of new subscriptions, outbound traffic, disk usage, etc. The AAD system can also generate an error model for estimating the error in the prediction model based on a comparison of the predicted resource usage to the actual resource usage...

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Abstract

A system for identifying abnormal resource usage in a data center is provided. In some embodiments, the system employs a prediction model for each of a plurality of resources and an abnormal resourceusage criterion. For each of a plurality of resources of the data center, the system retrieves current resource usage data for a current time and past resource usage data for that resource. The systemthen extracts features from the past resource usage data for that resource, predicts using the prediction model for that resource usage data for the current time based on the extracted features, anddetermines an error between the predicted resource usage data and the current resource usage data. After determining the error data for the resources, the system determines whether errors satisfy theabnormal resource usage criterion. If so, the system indicates that an abnormal resource usage has occurred

Description

Background technique [0001] A public cloud computing system ("cloud") provides shared computing resources for use by customers. Cloud computing resources are hardware and software resources. Hardware resources include components of the server, such as cores of a central processing unit (CPU), a graphics processing unit (GPU), main memory, secondary storage, and the like. Software resources include operating systems, database systems, accounting applications, etc. A typical cloud may have several data centers in different locations around the world. Each data center can host tens of thousands of servers. [0002] In order to use the cloud, a customer typically purchases a subscription to a service that uses the cloud. When purchasing a subscription, the customer may provide billing information and be provided with an account, which may be accessed using login information such as a username and password. To encourage users to become customers, cloud providers can offer vari...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/34G06F11/30G06N20/00
CPCG06F11/3495G06F11/3409G06F11/3082G06F11/3006G06N20/10G06N20/20G06N20/00G06N5/01G06F11/3452G06F11/3051G06F11/3447G06F11/00G06F11/006G06F2201/86G06N5/04
Inventor H·纽维尔斯-特勒姆A·希尔布驰S·B·纳哈姆Y·芬克尔斯泰恩D·阿隆E·勇姆-托维
Owner MICROSOFT TECH LICENSING LLC