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