Integrating Proactive and Reactive Approaches for Robust Real-Time Data Services

— Real-time data services are needed in data-intensive real-time applications such as e-commerce or traffic control. However, it is challenging to support real-time data services, if workloads dynamically change based on the market or traffic status. To enhance the quality of real-time data services even in the presence of dynamic workloads, feedback control theory has been applied. However, a major drawback of feedback control is that it only reacts to performance errors. To improve the robustness of realtime data services, we develop a statistical feed-forward approach that proactively adapts the incoming load, if necessary, to support the desired real-time data service delay. Further, we integrate it with a feedback controller to compensate potential prediction errors and adjust the system behavior in a reactive manner for timely data services. Performance evaluation results acquired in our real-time data service testbed show that our integrated approach considerably reduces the...

• Type: Conference
• Year: 2009
• Where: RTSS
• Authors: Yan Zhou, Kyoung-Don Kang
• Keywords: Applied Computing, Data-intensive Real-time Applications, Feedback Control, Real-time Data Service, RTSS 2009