• DocumentCode
    1931830
  • Title

    An Approach for Harmonizing Conflicting Policies in Multiple Self-Adaptive Modules

  • Author

    Wang, Hua ; Ying, Jing

  • Author_Institution
    Zhejiang Univ., Hangzhou
  • Volume
    4
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    2379
  • Lastpage
    2384
  • Abstract
    A recent approach to monitor and adapt system behavior at runtime is to decouple one or more external modules and self-adaptive mechanism from the target system. An important challenge arises when more than one such self-adaptive module is employed: how can we ensure that they cooperate without conflicts in a coherent fashion? This paper describes our initial approach for harmonizing conflicting policies in the presence of multiple self-adaptive modules. The main distribution of the paper is to resolve conflicts using an extended ECA rule paradigm to coordinate self-adaptive actions among multiple external modules. The approach shares advantages with other policy languages, i.e., the declarative and domain-independent semantics of policy rules. However, a key benefit of our approach is that both conflicting actions and influence of actions are considered. We focus on the problem of harmonizing self-adaptation capability by detecting and further resolving policy conflicts using action-level meta rule and value-level meta rule. Finally, this paper illustrates the efficiency of the approach in a VOD system as a case study, and discusses our future plans.
  • Keywords
    programming language semantics; self-adjusting systems; software architecture; action-level meta rule; adapt system behavior; conflicting policy harmonizing architecture; domain-independent semantics; extended ECA rule paradigm; multiple self-adaptive modules; Computer science; Computerized monitoring; Condition monitoring; Control systems; Cybernetics; Educational institutions; Logic; Machine learning; Programming profession; Software systems; ECA rule; Policy; Policy conflict; Self-adaptation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370543
  • Filename
    4370543