Commercial applications of grid computing
Performance analysis and grid computing
Parameter inference of queueing models for IT systems using end-to-end measurements
Performance Evaluation
Scalability of the Nutch search engine
Proceedings of the 21st annual international conference on Supercomputing
CPU demand for web serving: Measurement analysis and dynamic estimation
Performance Evaluation
Real-time performance modeling for adaptive software systems
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
Enhanced inferencing: estimation of a workload dependent performance model
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
Tracking adaptive performance models using dynamic clustering of user classes
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
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The answers to many important performance relatedquestions with multiclass queueing models depends uponhaving estimates for the service times of different classesof jobs. We present a general approach to infer the per-classservice times at different servers in an environmentwhere only server throughput, utilization and per-class responsetime measurements are available. The per-classservice times are solutions to an optimization problemwith queueing-theoretic formulas in the objective and constraints.We further study the impact of the variance of servicetimes on the variance of response times. A few casestudies are presented to demonstrate the power of our approach.