TITLE

The Effect of Real-valued Negative Selection Algorithm on Web Server Aging Detection

AUTHOR(S)
Yiwen Liang; Huan Yang; Jun Fu; Chengyu Tan; Aolin Liu; Shiwen Zhu
PUB. DATE
April 2012
SOURCE
Journal of Software (1796217X);Apr2012, Vol. 7 Issue 4, p849
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Several researchers have reported the fact that web server systems executing continuously for a long time show a degradation of their performance, and/or an increased occurrence rate of hang/crash failures. This phenomenon has been called 'web server aging'. To avoid this problem, it becomes an important issue to detect web server aging in web server maintenance. Existing technologies depending on aging samples succeed in detecting known web server aging, but fail to detect novel aging because of the nondeterministic nature of the web server aging. Given that normal samples are much easier to acquire from running web server than aging samples, this paper proposed an immune-inspired real-valued negative selection algorithm to detect previously unseen web server aging, it only needs normal samples to train detectors that have the ability to classify a novel sample as web server aging or not. The basis of the detection is aging causes performance deviation from the normal state. Preliminary experimental results showed that the method could improve the performance of the detection of novel web server aging without responding to normal status.
ACCESSION #
76109693

 

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