Abstract
According to the characteristic of performance parameters of application sever, a new software aging prediction model based on wavelet network is proposed. The dimensionality of input variables is reduced by principal component analysis, and the parameters of wavelet network are optimized with adaptive particle swarm optimization (PSO) algorithm. The objective is to observe and model the existing systematic parameter data series of application server to predict accurately future unknown data values. By the model, we can get the aging threshold before application server fails and rejuvenate the application server in autonomic ways before observed 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 wavelet network with adaptive PSO algorithm is effective and more accurate than wavelet network model with Genetic algorithm (GA).
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References
Garg, S., Puliafito, A., Telek, M., Trivedi, K.S.: A Methodology for Detection and Estima-tion of Software Aging. In: Int. Symp. On Software Reliability Engineering, ISSRE (1998)
Huang, Y., Kintala, C., Kolettis, N., Fulton, N.: Software Rejuvenation: Analysis, Module and Applications. In: IEEE Int. Symposium on Fault Tolerant Computing, FTCS 25 (1995)
Chillarege, R., Biyani, S., Rosenthal, J.: Measurement of failure rate in widely distributed software. In: Proc. of 25th IEEE Intl. Symposium on Fault-Tolerant Computing, pp. 424–433. Pasadena, CA (1995)
Tang, D., Iyer, R.K.: Dependability Measurement Modeling of a Multicomputer System. IEEE Transactions on Computers, 31 (1993)
Lin, T.T., Siewiorek, D.P.: Error Log Analysis: Statistical Modeling and Heuristic Trend Analysis. IEEE Transactions on Reliability 39, 419–432 (1990)
Amir, B.: Geva: Scalenet-Multiscale Neural network Architecture For Time Series Prediction. IEEE Transactions on Neural Networks 9, 1471–1482 (1998)
Rattan, Sanjay, S.P., Hsieh, William, W.: Complex-valued Neural Networks for Nonlinear Complex Principal Component Analysis. Neural Networks 18(1), 61–69 (2005)
Zhang, Q., Benvenise, A.: Wavelet Network. IEEE Transactions on Neural Network 3, 889–898 (1992)
Bashir, Z., El-Hawary, M.E.: Short Term Load Forecasting By Using Wavelet Neural Net-works. In: The IEEE Conference on Electrical and Computer Engineering, Canadian, pp. 163–166. IEEE Computer Society Press, Los Alamitos (2000)
Meng, H.N., Qi, Y., Hou, D. (ed.): Study on Application Server Aging Prediction based on Wavelet Network with Hybrid Genetic Algorithm. In: International Symposium on Parallel and Distributed Processing and Applications, Sorrento, Italy, 573–583 (2006)
Chris, C., Holmes, B., Mallick, K.: Bayesian Wavelet Networks for Nonparametric Regression. IEEE transactions on neural networks 11 (2000)
Zhang, X. (ed.): Robust Multiwavelets Support Vector Regression Network. In: International Con-ference on Control and Automation, Budapest, Hungary, pp. 27–29 (2005)
Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, Perth, Australia, pp. 942–1948. IEEE Computer Society Press, Los Alamitos (1995)
Zhang, C., Shao, H., Li, Y.: Particle swarm optimization for evolving artificial neural network. In: Proceedings of the IEEE International Conference on Systems, Man, And Cybernetics, vol. 4, pp. 2487–2490 (2000)
Settles, M., Ryiander, B.: Neural Network Learning using Particle Swarm Optimizers. Advances in Information Science and Soft Computing , 224–226 (2002)
Meng, H.N., Qi, Y., Hou, D.: Software Aging Prediction Model based on Fuzzy Wavelet Network with Adaptive Genetic Algorithm. In: 18th IEEE International Conference on Tools with Artificial Intelligence, IEEE Computer Society Press, Los Alamitos (2006)
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Ning, M.H., Yong, Q., Di, H., Xia, P.L., Ying, C. (2007). Application Server Aging Prediction Model Based on Wavelet Network with Adaptive Particle Swarm Optimization Algorithm. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2007. Lecture Notes in Computer Science(), vol 4682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74205-0_3
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DOI: https://doi.org/10.1007/978-3-540-74205-0_3
Publisher Name: Springer, Berlin, Heidelberg
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