Modeling Uncertainty for Middleware-based Streaming Power Grid Applications
Ilge Akkaya, Edward A. Lee, Yan Liu, Ian Gorton

Citation
Ilge Akkaya, Edward A. Lee, Yan Liu, Ian Gorton. "Modeling Uncertainty for Middleware-based Streaming Power Grid Applications". MW4NG'13: 8th International Workshop on Middleware for Next Generation Internet Computing, 9, December, 2013.

Abstract
The power grid is incorporating high throughput sensor devices into power distribution networks. The future power grid needs to guarantee accuracy and responsiveness of applications that consume data from multiple sensor streams. The end-to-end performance and overall scalability of cyber-physical energy applications depend on the middleware's ability to handle multi-source sensor data, which exhibits uncertain behavior under highly variable numbers of sensors and middleware topologies. In this paper, we present a parametric approach to model middleware uncertainty and to analyze its effect on distributed power applications. The models encapsulate the entire dataflow paths from sensor devices, through network and middleware components to the power application nodes that utilize sensor data streams. Using the Ptolemy II framework for modeling and simulation, we generate Monte Carlo samples of uncertain parameters that are used to generate parameterized middleware models that are used in end-to-end Discrete-Event (DE) system simulation simulation. The simulation results are further analyzed using regression methods to reveal the parameters that are influential in the limiting middleware behavior to achieve temporal requirements of the power applications.

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Citation formats  
  • HTML
    Ilge Akkaya, Edward A. Lee, Yan Liu, Ian Gorton. <a
    href="http://www.terraswarm.org/pubs/139.html"
    >Modeling Uncertainty for Middleware-based Streaming
    Power Grid Applications</a>, MW4NG'13: 8th
    International Workshop on Middleware for Next Generation
    Internet Computing, 9, December, 2013.
  • Plain text
    Ilge Akkaya, Edward A. Lee, Yan Liu, Ian Gorton.
    "Modeling Uncertainty for Middleware-based Streaming
    Power Grid Applications". MW4NG'13: 8th International
    Workshop on Middleware for Next Generation Internet
    Computing, 9, December, 2013.
  • BibTeX
    @inproceedings{AkkayaLeeLiuGorton13_ModelingUncertaintyForMiddlewarebasedStreamingPower,
        author = {Ilge Akkaya and Edward A. Lee and Yan Liu and Ian
                  Gorton},
        title = {Modeling Uncertainty for Middleware-based
                  Streaming Power Grid Applications},
        booktitle = {MW4NG'13: 8th International Workshop on Middleware
                  for Next Generation Internet Computing},
        day = {9},
        month = {December},
        year = {2013},
        abstract = {The power grid is incorporating high throughput
                  sensor devices into power distribution networks.
                  The future power grid needs to guarantee accuracy
                  and responsiveness of applications that consume
                  data from multiple sensor streams. The end-to-end
                  performance and overall scalability of
                  cyber-physical energy applications depend on the
                  middleware's ability to handle multi-source sensor
                  data, which exhibits uncertain behavior under
                  highly variable numbers of sensors and middleware
                  topologies. In this paper, we present a parametric
                  approach to model middleware uncertainty and to
                  analyze its effect on distributed power
                  applications. The models encapsulate the entire
                  dataflow paths from sensor devices, through
                  network and middleware components to the power
                  application nodes that utilize sensor data
                  streams. Using the Ptolemy II framework for
                  modeling and simulation, we generate Monte Carlo
                  samples of uncertain parameters that are used to
                  generate parameterized middleware models that are
                  used in end-to-end Discrete-Event (DE) system
                  simulation simulation. The simulation results are
                  further analyzed using regression methods to
                  reveal the parameters that are influential in the
                  limiting middleware behavior to achieve temporal
                  requirements of the power applications. },
        URL = {http://terraswarm.org/pubs/139.html}
    }
    

Posted by Ilge Akkaya on 4 Oct 2013.

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