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KAF: Kalman filter based adaptive maintenance for dependability of composite services

  • Huipeng Guo*
  • , Jinpeng Huai
  • , Yang Li
  • , Ting Deng
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Service composition is fundamental in development of Web service oriented applications. Dependability of composite services is of significant importance since it directly impacts users' experience. However, dependability of a composite service may change over time as a result of inevitable changes in component services. In addition, users may also pose varying dependability requirements to meet different needs. It has become a big challenge to dynamically maintain the dependability of composite services. This paper proposes an innovative system called KAF that constructs a closed-loop control for adaptive maintenance of composite services. Modeling the control process as a Markov decision process (MDP), we further design an efficient Kalman-Filter based algorithm for service state prediction. With the availability of the precise prediction, optimal control decisions can be made. We evaluate the performance of KAF against other alternative approaches through comprehensive experiments and results demonstrate that KAF is capable for adaptive dependability maintenance.

Original languageEnglish
Title of host publicationAdvanced Information Systems Engineering - 20th International Conference, CAiSE 2008, Proceedings
Pages328-342
Number of pages15
DOIs
StatePublished - 2008
Event20th International Conference on Advanced Information Systems Engineering, CAiSE 2008 - Montpellier, France
Duration: 16 Jun 200820 Jun 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5074 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Advanced Information Systems Engineering, CAiSE 2008
Country/TerritoryFrance
CityMontpellier
Period16/06/0820/06/08

Keywords

  • Adaptive maintenance
  • Dependability
  • Kalman filter
  • Service composition

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