Uncertainty Analysis of Middleware Architectures for Streaming Smart Grid Applications
Ilge Akkaya, Yan Liu, Edward A. Lee

Citation
Ilge Akkaya, Yan Liu, Edward A. Lee. "Uncertainty Analysis of Middleware Architectures for Streaming Smart Grid Applications". IEEE Transactions on Services Computing, January 2016.

Abstract
Accuracy and responsiveness are two key properties of emerging cyber-physical energy systems (CPES) that need to incorporate high throughput sensor streams for distributed monitoring and control purposes. The electric power grid, which is a prominent example of such systems, is being integrated with high throughput sensors in order to support stable system dynamics that are provisioned to be utilized in real-time supervisory control applications. The end-to-end performance and overall scalability of cyber-physical energy applications depend on robust middleware that is able to operate with variable resources and multi-source sensor data. This leads to uncertain behavior under highly variable sensor and middleware topologies. We present a parametric approach to modeling middleware for distributed power applications and account for temporal satisfiability of system properties under network resource and data volume uncertainty. We present a heterogeneous modeling framework that combines Monte Carlo simulations of uncertainty parameters within an executable Discrete-Event (DE) middleware model. By employing Monte Carlo simulations followed by regression analysis, we determine system parameters that significantly affect limiting middleware behavior and the achievability of temporal requirements.

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Citation formats

• HTML

  Ilge Akkaya, Yan Liu, Edward A. Lee. <a
  href="http://www.terraswarm.org/pubs/594.html"
  >Uncertainty Analysis of Middleware Architectures for
  Streaming Smart Grid Applications</a>, <i>IEEE
  Transactions on Services Computing</i>, January 2016.

• Plain text

  Ilge Akkaya, Yan Liu, Edward A. Lee. "Uncertainty
  Analysis of Middleware Architectures for Streaming Smart
  Grid Applications". <i>IEEE Transactions on
  Services Computing</i>, January 2016.

• BibTeX

  @article{AkkayaLiuLee16_UncertaintyAnalysisOfMiddlewareArchitecturesForStreaming,
      author = {Ilge Akkaya and Yan Liu and Edward A. Lee},
      title = {Uncertainty Analysis of Middleware Architectures
                for Streaming Smart Grid Applications},
      journal = {IEEE Transactions on Services Computing},
      month = {January},
      year = {2016},
      abstract = {Accuracy and responsiveness are two key properties
                of emerging cyber-physical energy systems (CPES)
                that need to incorporate high throughput sensor
                streams for distributed monitoring and control
                purposes. The electric power grid, which is a
                prominent example of such systems, is being
                integrated with high throughput sensors in order
                to support stable system dynamics that are
                provisioned to be utilized in real-time
                supervisory control applications. The end-to-end
                performance and overall scalability of
                cyber-physical energy applications depend on
                robust middleware that is able to operate with
                variable resources and multi-source sensor data.
                This leads to uncertain behavior under highly
                variable sensor and middleware topologies. We
                present a parametric approach to modeling
                middleware for distributed power applications and
                account for temporal satisfiability of system
                properties under network resource and data volume
                uncertainty. We present a heterogeneous modeling
                framework that combines Monte Carlo simulations of
                uncertainty parameters within an executable
                Discrete-Event (DE) middleware model. By employing
                Monte Carlo simulations followed by regression
                analysis, we determine system parameters that
                significantly affect limiting middleware behavior
                and the achievability of temporal requirements.},
      URL = {http://terraswarm.org/pubs/594.html}
  }
  

Posted by Ilge Akkaya on 23 Jul 2015.
Groups: services