Citation
"Coordinated Actors for Reliable Self-Adaptive Systems". Springer, October, 2016; Formal Aspects of Component Software (FACS) - The 13th International Conference, Besançon, France, Oct. 19-21, 2016.

Abstract
Self-adaptive systems are systems that automatically adapt in response to environmental and internal changes, such as possible failures and variations in resource availability. Such systems are often realized by a MAPE-K feedback loop, where Monitor, Analyze, Plan and Execute components have access to a runtime model of the system and environment which is kept in the Knowledge component. In order to provide guarantees on the correctness of a self-adaptive system at runtime, the MAPE-K feedback loop needs to be extended with assurance techniques. To address this issue, we propose a coordinated actor-based approach to build a reusable and scalable model@runtime for self-adaptive systems in the domain of track-based traffic control systems. We demonstrate the approach by implementing an automated Air Traffic Control system (ATC) using Ptolemy tool. We compare different adaptation policies on the ATC model based on performance metrics and analyze combination of policies in different configurations of the model. We enriched our framework with runtime performance analysis such that for any unexpected change, subsequent behavior of the model is predicted and results are used for adaptation at the change-point. Moreover, the developed framework enables checking safety properties at runtime.

Electronic downloads

• BagheriEtAl_CoordinatedActors_FACS_2016.pdf · application/x-octet-stream · 658 kbytes
• https://doi.org/10.1007/978-3-319-57666-4

• HTML

   <a
  href="http://chess.eecs.berkeley.edu/pubs/1181.html"
  ><i>Coordinated Actors for Reliable Self-Adaptive
  Systems</i></a>, Springer, October, 2016; Formal
  Aspects of Component Software (FACS) - The 13th
  International Conference, Besançon, France,
  Oct. 19-21, 2016.

• Plain text

   "Coordinated Actors for Reliable Self-Adaptive
  Systems". Springer, October, 2016; Formal Aspects of
  Component Software (FACS) - The 13th International
  Conference, Besançon, France, Oct. 19-21, 2016.

• BibTeX

  @proceedings{16_CoordinatedActorsForReliableSelfAdaptiveSystems,
      title = {Coordinated Actors for Reliable Self-Adaptive
                Systems},
      organization = {Springer},
      month = {October},
      year = {2016},
      note = {Formal Aspects of Component Software (FACS) - The
                13th International Conference, Besançon, France,
                Oct. 19-21, 2016.},
      abstract = {Self-adaptive systems are systems that
                automatically adapt in response to environmental
                and internal changes, such as possible failures
                and variations in resource availability. Such
                systems are often realized by a MAPE-K feedback
                loop, where Monitor, Analyze, Plan and Execute
                components have access to a runtime model of the
                system and environment which is kept in the
                Knowledge component. In order to provide
                guarantees on the correctness of a self-adaptive
                system at runtime, the MAPE-K feedback loop needs
                to be extended with assurance techniques. To
                address this issue, we propose a coordinated
                actor-based approach to build a reusable and
                scalable model@runtime for self-adaptive systems
                in the domain of track-based traffic control
                systems. We demonstrate the approach by
                implementing an automated Air Traffic Control
                system (ATC) using Ptolemy tool. We compare
                different adaptation policies on the ATC model
                based on performance metrics and analyze
                combination of policies in different
                configurations of the model. We enriched our
                framework with runtime performance analysis such
                that for any unexpected change, subsequent
                behavior of the model is predicted and results are
                used for adaptation at the change-point. Moreover,
                the developed framework enables checking safety
                properties at runtime.},
      URL = {http://chess.eecs.berkeley.edu/pubs/1181.html}
  }
  

Posted by Mary Stewart on 3 Oct 2016.
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