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Event-Driven Quality of Service Prediction

  • Liangzhao Zeng
  • Christoph Lingenfelder
  • Hui Lei
  • Henry Chang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5364)

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.

Keywords

Event Sequence Target Time Exponential Smoothing Service Instance Service Prediction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Liangzhao Zeng
    • 1
  • Christoph Lingenfelder
    • 1
  • Hui Lei
    • 1
  • Henry Chang
    • 1
  1. 1.IBM T.J. Watson Research Center Yorktown Heights

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