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Date of Publication:2015-01-01

Journal:华中科技大学学报 自然科学版

Affiliation of Author(s):电子信息与电气工程学部

Issue:5

Page Number:63-67

ISSN No.:1671-4512

Abstract:A method based on multi‐attribute information entropy was proposed to detect anomalous states of virtual machines in cloud computing environments .Firstly ,the 2‐norm of several attributes characterizing the states of a virtual machine was computed for each sampled data .Then ,the joint in‐formation entropy was computed based on the occurrence frequency of each 2‐norm value in a fixed pe‐riod of time .Once the entropy reached its maximum ,the anomaly detection function in the proposed method was activated .During the anomaly detection ,the moving weighted average and the variance of the 2‐norm sequence were used to construct the test variable ,and the non‐parametric CUSUM algo‐rithm was adopted to complete the anomaly detection .Experimental results based on Hadoop show that the method can not only reduce false alarms caused by accidental and transient anomalous states , but also give accurate alarms before the significant anomalous state occurs .

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