Dissertation (Metadata)
Title:Self-Adaptive Performance Monitoring for Component-Based Software Systems
 
Author:Jens Ehlers
 
URN:NBN:urn:nbn:de:gbv:8-diss-84142
 
Faculty:Faculty of Engineering
DDC:004 Computer science
 
Date of thesis defense:2012-04-20
 
Referent:Prof. Dr. Wilhelm Hasselbring
second reviewer(s) :Prof. Dr. Florian Matthes
 
Description: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.
 
Keywords:software performance, adaptive monitoring, failure diagnosis, anomaly detection
 
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