Citation
Ilge Akkaya, Yan Liu, Edward A. Lee. "Uncertainty Analysis of Middleware Services for Streaming Smart Grid Applications". IEEE Transactions on Services Computing, September 2015.

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 applications. 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 services that are 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 the middleware service architecture 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 service model. By employing Monte Carlo simulations followed by regression analysis, we quantify system parameters that significantly affect behavior of middleware services and the achievability of temporal requirements.

Electronic downloads

• http://dx.doi.org/10.1109/TSC.2015.2456888

• HTML

  Ilge Akkaya, Yan Liu, Edward A. Lee. <a
  href="http://chess.eecs.berkeley.edu/pubs/1149.html"
  >Uncertainty Analysis of Middleware Services for
  Streaming Smart Grid Applications</a>, <i>IEEE
  Transactions on Services Computing</i>, September 2015.

• Plain text

  Ilge Akkaya, Yan Liu, Edward A. Lee. "Uncertainty
  Analysis of Middleware Services for Streaming Smart Grid
  Applications". <i>IEEE Transactions on Services
  Computing</i>, September 2015.

• BibTeX

  @article{AkkayaLiuLee15_UncertaintyAnalysisOfMiddlewareServicesForStreamingSmart,
      author = {Ilge Akkaya and Yan Liu and Edward A. Lee},
      title = {Uncertainty Analysis of Middleware Services for
                Streaming Smart Grid Applications},
      journal = {IEEE Transactions on Services Computing},
      number = {X},
      month = {September},
      year = {2015},
      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
                applications. 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 services that are 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 the middleware service architecture 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 service model. By employing Monte
                Carlo simulations followed by regression analysis,
                we quantify system parameters that significantly
                affect behavior of middleware services and the
                achievability of temporal requirements.},
      URL = {http://chess.eecs.berkeley.edu/pubs/1149.html}
  }
  

Posted by Mary Stewart on 5 Nov 2015.
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