000K  utf8
1100  $c2012
1500  eng
2050  urn:nbn:de:gbv:8-diss-84142
3000  Ehlers, Jens
4000  Self-Adaptive Performance Monitoring for Component-Based Software Systems$hChristian-Albrechts-Universität zu Kiel  [Ehlers, Jens]
4030  Kiel$nChristian-Albrechts-Universität zu Kiel
4209  Effective monitoring of a software system’s runtime behavior is necessary to evaluate the compliance of performance objectives. This thesis has emerged in the context of the Kieker framework addressing application performance monitoring. The contribution includes a self-adaptive performance monitoring approach allowing for dynamic adaptation of the monitoring coverage at runtime. The monitoring data includes performance measures such as throughput and response time statistics, the utilization of system resources, as well as the inter- and intra-component control flow. Based on this data, performance anomaly scores are computed using time series analysis and clustering methods. The self-adaptive performance monitoring approach reduces the business-critical failure diagnosis time, as it saves time-consuming manual debugging activities. The approach and its underlying anomaly scores are extensively evaluated in lab experiments.
4950  https://nbn-resolving.org/urn:nbn:de:gbv:8-diss-84142$xR$3Volltext$534
4961  https://macau.uni-kiel.de/receive/diss_mods_00008414
5051  004
5550  adaptive monitoring
5550  anomaly detection
5550  failure diagnosis
5550  software performance