Self-Adaptive Software System Monitoring for Performance Anomaly Localization
Ehlers, Jens, van Hoorn, André, Waller, Jan and Hasselbring, Wilhelm (2011) Self-Adaptive Software System Monitoring for Performance Anomaly Localization [Paper] In: 8th IEEE/ACM International Conference on Autonomic Computing (ICAC '11), June 14-18, 2011, Karlsruhe, Germany . Proceedings of the 8th IEEE/ACM International Conference on Autonomic Computing (ICAC '11) ; pp. 197-200 .
icac2011_jeh_avh_jwa_wha.pdf - Accepted Version
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Autonomic computing components and services require continuous monitoring capabilities for collecting and analyzing data of runtime behavior. Particularly for software systems, a trade-off between monitoring coverage and performance overhead is necessary.
In this paper, we propose an approach for localizing performance anomalies in software systems employing self-adaptive monitoring. Time series analysis of operation response times, incorporating architectural information about the diagnosed software system, is employed for anomaly localization. Comprising quality of service data, such as response times, resource utilization, and anomaly scores, OCL-based monitoring rules specify the adaptive monitoring coverage. This enables to zoom into a system's or component's internal realization in order to locate root causes of software failures and to prevent failures by early fault determination and correction.
The approach has been implemented as part of the Kieker monitoring and analysis framework. The evaluation presented in this paper focuses on monitoring overhead, response time forecasts, and the anomaly detection process.
|Document Type:||Conference or Workshop Item (Paper)|
|Research affiliation:||Kiel University > Faculty of Engineering > Department of Computer Science > Software Engineering|
|Date Deposited:||18 Feb 2012 06:05|
|Last Modified:||22 Oct 2012 08:25|
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