Abstract
We present an approach to compute the quality of prediction for network monitoring. The monitoring is part of a proactive mobile agents based management system for network health (magmaNH). To allow prediction of a system’s behavior, magmaNH contains prediction services placed on core nodes of a network. To make predictions as precise as possible, a measure and a process have to be defined, which enable to determine the quality of predictions. This measure of quality enables magmaNH optimizing the prediction services to become a reliable support system for automated network management.
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References
Murphy, B., Gent, T.: Measuring System and Software Reliability using an Automated Data Collection Process. In: Quality and Reliability Engineering International, pp. 341–353 (1995)
Valiant, L.: A theory of the learnable. Communication of the ACM 27(11), 1134–1142 (1994)
Schuurmans, D., Greiner, R.: Practical PAC Learning. In: Proceedings of the Fourteenth International Conference on Artificial Intelligence, IJCAI 1995 (1995)
Bajić, V.B.: Comparing the success of different prediction software in sequence analysis: a review. Briefings in Bioinformatics 1(3), 214–228 (2000)
Goldszmidt, G.: On Distributed System Management. In: Proceedings of the Third IBM/CAS Conference, Toronto, Canada (1993)
Herrmann, K., Zapf, M.: The AMETAS White Paper Series (July 2000), http://www.accsis.com/ametas/docs/white/AllWhite.pdf
Hegering, H.-G., Abeck, S., Neumair, B.: Integrated Management of Networked Systems. Morgan Kaufman, San Francisco (1999)
Schulz, S., Herrmann, K., Geihs, K.: HEAT - A Health Agent-Toolbox for Distributed Network Management. In: Proceedings of the 10th annual Workshop of HP OpenView University Association, Geneva, Switzerland (2003)
Herrmann, K., Geihs, K.: Integrating mobile agents and neural networks for proactive management. In: IFIP International Working Conference on Distributed Applications and Interoperable Systems (DAIS 2001), Krakow, Poland, Chapman-Hall, Boca Raton (2001)
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Schulz, S., Schulz, M., Tanner, A. (2004). Frame of Interest Approach on Quality of Prediction for Agent-Based Network Monitoring. In: Müller-Schloer, C., Ungerer, T., Bauer, B. (eds) Organic and Pervasive Computing – ARCS 2004. ARCS 2004. Lecture Notes in Computer Science, vol 2981. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24714-2_19
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DOI: https://doi.org/10.1007/978-3-540-24714-2_19
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