Abstract
We propose a new paradigm for software availability enhancement. We offer a two-step strategy: Failure prediction followed by maintenance actions with the objective of avoiding impending failures or minimizing the effort of their repair. For the first step we present two failure prediction methods: universal basis functions (UBF) and similar events prediction (SEP), which are based on probabilistic analysis. The potential of the presented methods is evaluated by a case-study where failures of a commercial telecommunication platform have been predicted. The second step includes existing maintenance methods fitting the proposed approach and a new recovery strategy called “adaptive recovery blocks”. Since system availability enhancement is the overall goal, equations to calculate availability of such a system are given as well.
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References
Sullivan, M., Chillarege, R.: Software defects and their impact on system availability -a study of field failures in operating systems. In: 21st Int. Symp. on Fault-Tolerant Computing (FTCS-21), pp. 2–9 (1991)
Garg, S., Puliafito, A., Telek, M., Trivedi, K.S.: Analysis of Preventive Maintenance in Transactions Based Software Systems. IEEE Trans. Comput. 47(1), 96–107 (1998)
Huang, Y., Kintala, C., Kolettis, N., Fulton, N.: Software Rejuvenation: Analysis, Module and Applications. In: Proceedings of IEEE Intl. Symposium on Fault Tolerant Computing, FTCS 25 (1995)
Dohi, T., Goseva-Popstojanova, K., Trivedi, K.S.: Statistical Non-Parametric Algorihms to Estimate the Optimal Software Rejuvenation Schedule. In: Proceedings of the Pacific Rim International Symposium on Dependable Computing, PRDC (2000)
Garg, S., van Moorsel, A., Vaidyanathan, K., Trivedi, K.S.: A Methodology for Detection and Estimation of Software Aging. In: Proceedings of the Int’l. Symp. on Software Reliability Engineering, ISSRE (1998)
Vaidyanathan, K., Trivedi, K.S.: A Measurement-Based Model for Estimation of Resource Exhaustion in Operational Software Systems. In: Proceedings of the International Symposium on Software Reliability Engineering, ISSRE (1999)
Li, L., Vaidyanathan, K., Trivedi, K.S.: An Approach for Estimation of Software Aging in a Web Server. In: Proceedings of the Intl. Symposium on Empirical Software Engineering, ISESE (2002)
Fox, A., Kiciman, E., Patterson, D., Katz, R., Jordan, M., Stoica, I.: Statistical Monitoring + Predictable Recovery = Self-*. In: Proceedings of the Internation Workshop on Self-* Properties in Complex Information Systems, SELF-STAR (2004)
Lin, T., Siewiorek, D.P.: Error log analysis: statistical modeling and heuristic trend analysis. IEEE Transactions on Reliability 39(4), 419–432 (1990)
Salfner, F., Tschirpke, S., Malek, M.: Comprehensive Logfiles for Autonomic Systems. In: Proceedings of 9th IEEE Workshop on Fault-Tolerant Parallel, Distributed and Network-Centric Systems (2004)
Geman, S., Bienenstock, E., Doursat, R.: Neural Networks and the Bias/Variance Dilemma. Neural computation 4(1), 1–58 (1992)
Weigend, A.S., Gershenfeld, N.A. (eds.): Time Series Prediction, 1st edn. Addison-Wesley, Reading (1994)
Hoffmann, G.A., Salfner, F., Malek, M.: Advanced Failure Prediction in Complex Software Systems. Research report 172, Department of Computer Science, Humboldt University, Berlin, Germany (2004), Available at: www.informatik.hu-berlin.de/~salfner
Hoffmann, G.A.: Adaptive Transfer Functions in Radial Basis Function Networks (RBF). In: International Conference on Computational Science (2004)
Schoelkopf, B., Smola, A.: Learning with Kernels. MIT Press, Cambridge (2002)
Malek, M., Salfner, F., Hoffmann, G.A.: Self-Rejuvenation - an Effective Way to High Availability. In: SELF-STAR: International Workshop on Self-* Properties in Complex Information Systems (2004)
Castelli, V., Harper, R.E., Heidelberger, P., Hunter, S.W., Trivedi, K.S., Vaidyanathan, K., Zeggert, W.P.: Proactive management of software aging. IBM Journal of Research and Development 45(2), 311–332 (2001)
Pfening, A., Garg, S., Puliafito, A., Telek, M., Trivedi, K.S.: Optimal Software Rejuvenation for Tolerating Soft Failures. Performance Evaluation 27, 28 (1996)
Garg, S., Telek, M., Puliafito, A., Trivedi, K.S.: Analysis of Software Rejuvenation using Markov Regenerative Stochastic Petri Net. In: Proceedings of the International Symposium on Software Reliability Engineering, ISSRE 1995 (1995)
Trivedi, K.S., Vaidyanathan, K., Goseva-Popstojanova, K.: Modeling and Analysis of Software Aging and Rejuvenation. In: Proceedings of the IEEE Annual Simulation Symposium (2000)
Randell, B.: System structure for software fault tolerance. IEEE Transactions on Software Engineering 1(2), 220–232 (1975)
Ferber, R.: Information Retrieval: Suchmodelle und Data-Mining-Verfahren für Textsammlungen und das Web. dpunkt.verlag, Heidelberg (2003)
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Salfner, F., Hoffmann, G., Malek, M. (2005). Prediction-Based Software Availability Enhancement. In: Babaoglu, O., et al. Self-star Properties in Complex Information Systems. SELF-STAR 2004. Lecture Notes in Computer Science, vol 3460. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428589_10
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DOI: https://doi.org/10.1007/11428589_10
Publisher Name: Springer, Berlin, Heidelberg
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