NDLI: Software Aging Prediction Model Based on Fuzzy Wavelet Network with Adaptive Genetic Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Meng Hai Ning Qi Yong Hou Di Chen Ying Zhao Ji Zhong
Copyright Year	2006
Description	Author affiliation: Sch. of Electron. & Inf. Eng., Xi'an Jiaotong Univ. (Meng Hai Ning; Qi Yong; Hou Di)
Abstract	According to the characteristics of the operational behavior and runtime state of application sever, the resource consumption time series are observed and modeled by fuzzy wavelet network (FWN) with fuzzy logic inference and learning capability. The objective is to model the extracted data series of systematic performance parameters to predict software aging in application server. The dimensionality of input variables of FWN is reduced by principal components analysis (PCA), and the structure and parameters of FWN are optimized with adaptive genetic algorithm (GA). Judging by the model, we can get the aging threshold before application server failed and preventively maintenance the application server before systematic parameter value reaches the threshold. The experiments are carried out to validate the efficiency of the proposed model and show that the aging prediction model based on FWN with adaptive genetic algorithm is superior to the neural network (NN) model and wavelet network (WN) model in the aspects of convergence rate and prediction precision
Starting Page	659
Ending Page	666
File Size	371843
Page Count	8
File Format	PDF
ISBN	0769527280
ISSN	10823409
DOI	10.1109/ICTAI.2006.104
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-11-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Aging Predictive models Adaptive systems Genetic algorithms Application software Network servers Fuzzy logic Principal component analysis Neural networks Runtime
Content Type	Text
Resource Type	Article

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