Correlating resource demand information with ARM data for application services
Proceedings of the 1st international workshop on Software and performance
Using regression splines for software performance analysis
Proceedings of the 2nd international workshop on Software and performance
Performance Guarantees for Web Server End-Systems: A Control-Theoretical Approach
IEEE Transactions on Parallel and Distributed Systems
TPC-W: A Benchmark for E-Commerce
IEEE Internet Computing
Parameter estimation for performance models of distributed application systems
CASCON '95 Proceedings of the 1995 conference of the Centre for Advanced Studies on Collaborative research
Workload Service Requirements Analysis: A Queueing Network Optimization Approach
MASCOTS '02 Proceedings of the 10th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
Self-Optimization in Computer Systems via On-Line Control: Application to Power Management
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
Hierarchical model-based autonomic control of software systems
DEAS '05 Proceedings of the 2005 workshop on Design and evolution of autonomic application software
Tracking time-varying parameters in software systems with extended Kalman filters
CASCON '05 Proceedings of the 2005 conference of the Centre for Advanced Studies on Collaborative research
The Use of Optimal Filters to Track Parameters of Performance Models
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
Parameter inference of queueing models for IT systems using end-to-end measurements
Performance Evaluation
Performance modeling and prediction of enterprise JavaBeans with layered queuing network templates
SAVCBS '05 Proceedings of the 2005 conference on Specification and verification of component-based systems
A Regression-Based Analytic Model for Dynamic Resource Provisioning of Multi-Tier Applications
ICAC '07 Proceedings of the Fourth International Conference on Autonomic Computing
CPU demand for web serving: Measurement analysis and dynamic estimation
Performance Evaluation
Automatic request categorization in internet services
ACM SIGMETRICS Performance Evaluation Review
Service System Resource Management Based on a Tracked Layered Performance Model
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
Workload Analysis and Demand Prediction of Enterprise Data Center Applications
IISWC '07 Proceedings of the 2007 IEEE 10th International Symposium on Workload Characterization
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
Performance model driven QoS guarantees and optimization in clouds
CLOUD '09 Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing
Estimating service resource consumption from response time measurements
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
A workload characterization study of the 1998 World Cup Web site
IEEE Network: The Magazine of Global Internetworking
Model-based performance testing (NIER track)
Proceedings of the 33rd International Conference on Software Engineering
Autonomic load-testing framework
Proceedings of the 8th ACM international conference on Autonomic computing
Mitigating DoS Attacks Using Performance Model-Driven Adaptive Algorithms
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Indirect estimation of service demands in the presence of structural changes
Performance Evaluation
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Estimation techniques have been largely applied to track hidden performance parameters (e.g. service demands) of web based software systems. In this paper we investigate dynamic multiclass modeling of such systems, with variable classes of service, aiming at finding a low complexity model yet with enough accuracy. We propose a combination of clustering algorithm and tracking filter for effective grouping of classes of services. The tracking estimator is based on a layered queuing model with parameters for CPU demands and the user load intensity of each class of service. Clustering uses the K-means algorithm. The target application is autonomic control of web clusters, where changes occur at different rates and amplitudes and at random time instants. Experiments show that the tracking is effective, and reveal good filter settings for different variations.