Performance Guarantees for Web Server End-Systems: A Control-Theoretical Approach
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Software Engineering
Feedback Control with Queueing-Theoretic Prediction for Relative Delay Guarantees in Web Servers
RTAS '03 Proceedings of the The 9th IEEE Real-Time and Embedded Technology and Applications Symposium
Performance analysis of distributed server systems
Performance analysis of distributed server systems
Feedback Control of Computing Systems
Feedback Control of Computing Systems
The role of ontologies in autonomic computing systems
IBM Systems Journal
IEEE Internet Computing
Hierarchical model-based autonomic control of software systems
DEAS '05 Proceedings of the 2005 workshop on Design and evolution of autonomic application software
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
Online response time optimization of Apache web server
IWQoS'03 Proceedings of the 11th international conference on Quality of service
New developments in state estimation for nonlinear systems
Automatica (Journal of IFAC)
A performance analysis method for autonomic computing systems
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Database replication policies for dynamic content applications
Proceedings of the 1st ACM SIGOPS/EuroSys European Conference on Computer Systems 2006
CPU demand for web serving: Measurement analysis and dynamic estimation
Performance Evaluation
Scalable adaptive web services
Proceedings of the 2nd international workshop on Systems development in SOA environments
An adaptive feedback controller for SIP server memory overload protection
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
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
Real-time performance modeling for adaptive software systems
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
Estimating service resource consumption from response time measurements
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
Change-point detection for black-box services
Proceedings of the eighteenth ACM SIGSOFT international symposium on Foundations of software engineering
Tracking adaptive performance models using dynamic clustering of user classes
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
Using observation ageing to improve markovian model learning in QoS engineering
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
Autonomic load-testing framework
Proceedings of the 8th ACM international conference on Autonomic computing
Cost-effective cloud HPC resource provisioning by building semi-elastic virtual clusters
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Mitigating DoS Attacks Using Performance Model-Driven Adaptive Algorithms
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Adaptive model learning for continual verification of non-functional properties
Proceedings of the 5th ACM/SPEC international conference on Performance engineering
Indirect estimation of service demands in the presence of structural changes
Performance Evaluation
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Autonomic control of a service system can take advantage of a performance model only if a way can be found to track the changes in the system. A Kalman Filter provides a framework for integrating various kinds of measured data, and for tracking changes in any time-varying system. This work evaluates the effectiveness of such a filter in tracking changes in performance parameters of a software system that occur at different rates and amplitudes. The time-varying system is a Web application deployed in a data centre with layered queuing resources, in which parameter variations happen at random instants. The tracking filter is based on a layered queuing model of this system, with parameters representing CPU demands and the user load intensity. Experiments were performed to evaluate the effectiveness of the filter in tracking the changes, and the requirements for the filter settings for fast and slow variations in the parameters. The target application is autonomic control of a service centre.