Event-Driven Quality of Service Prediction

  • Authors:
  • Liangzhao Zeng;Christoph Lingenfelder;Hui Lei;Henry Chang

  • Affiliations:
  • IBM T.J. Watson Research Center Yorktown Heights NY 10598;IBM T.J. Watson Research Center Yorktown Heights NY 10598;IBM T.J. Watson Research Center Yorktown Heights NY 10598;IBM T.J. Watson Research Center Yorktown Heights NY 10598

  • Venue:
  • ICSOC '08 Proceedings of the 6th International Conference on Service-Oriented Computing
  • Year:
  • 2008

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Abstract

Quality of Service Management (QoSM) is a new task in IT-enabled enterprises that supports monitoring, collecting and predicting QoS data. QoSM solutions must be able to efficiently process runtime events, compute and pre dict QoS metrics, and provide real-time visibility and prediction of key perform ance indicators (KPI). Currently, most QoSM systems focus on moni tor ing of QoS constraints, i.e., they report what has been happened. In a way, this provides the awareness of past developments and sets the basis for decisions. However, this kind of knowledge is afterwit. For example, it cannot provide early warnings to prevent the QoS degradation or the violation of commitments. In this paper, we move one step forward to provide QoS prediction. We argue that performance metrics and KPIs can be predicted based on historical data. We present the design and implementation of a novel event-driven QoS prediction system. Integrated into the SOA infrastructure at large, the prediction system can process operational service events in a real-time fashion, in order to predict or refine the prediction of metrics and KPIs.