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Neural Adaptive Control in Application Service Management Environment

  • Tomasz Sikora
  • George D. Magoulas
Part of the Communications in Computer and Information Science book series (CCIS, volume 311)

Abstract

This paper presents a method and a framework for adaptive control in Application Service Management environments. The controlled system is treated as a “black-box” by observing its operation during normal work or load conditions. Run-time metrics are collected and persisted creating a Knowledge Base of actual system states. Equipped with such knowledge we define system inputs, outputs and effectively select high/low Service Level Agreements values, and good/bad control actions from the past. On the basis of gained knowledge a training set is constructed, which determines the operation of a neural controller deployed in the application run-time. Control actions are executed in the background of the current system state, which is then again monitored and stored extending the states repository, giving views on the appropriateness of the control, which is frequently evaluated.

Keywords

Application Service Management Adaptive Controller Service Level Agreement Knowledge Base Neural Networks Performance Metrics 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Tomasz Sikora
    • 1
  • George D. Magoulas
    • 1
  1. 1.Department of Computer Science and Information SystemsBirkbeck, University of LondonLondonUK

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