On the Use of Online Analytic Performance Models, in Self-Managing and Self-Organizing Computer Systems

Current computing environments are becoming increasingly complex in nature and exhibit unpredictable workloads. These environments create challenges to the design of systems that can adapt to changes in the workload while maintaining desired QoS levels. This paper focuses on the use of online analytic performance models in the design of self-managing and self-organizing computer systems. A general approach for building such systems is presented along with the algorithms used by a Quality of Service (QoS) controller. The robustness of the approach with respect to the variability of the workload and service time distributions is evaluated. The use of an adaptive controller that uses workload forecasting is discussed. Finally, the paper shows how online performance models can be used to design QoS-aware service oriented architectures.