An integrated feedback control approach for proportional slowdown differentiation on Internet servers

On Internet servers, there is an increasing demand for provisioning of fine-grained quality of service (QoS). Feedback control provides a sound way for such QoS provisioning by amortizing the effect of disturbances from unpredictable and dynamic server workloads. The performance of a feedback control approach is dependent on its agility to the workload changes. Queueing-model based prediction is effective in improving the agility. In this paper, we present a feedback control approach to manage the processing rate on Internet servers for QoS provisioning with respect to slowdown. Slowdown is the ratio of a request´s queueing delay to its service time and reflects the requirement that all requests should be treated equally regardless of their resource requirements. The approach adjusts the processing rate of a class using an integral feedback controller according to measured deviations from the target slowdown ratios. For agility, a queueing-model based predictor is integrated to periodically estimates the processing rate of the class. The experimental results under various environment settings demonstrate the approach´s effectiveness, robustness, and agility in providing proportional slowdown differentiation services.