Context Aware System Design
Christine Chan, Michael Ostertag, Alper Sinan Akyurek, Tajana Simunic Rosing

Citation
Christine Chan, Michael Ostertag, Alper Sinan Akyurek, Tajana Simunic Rosing. "Context Aware System Design". SPIE Defense and Security, International Society for Optics and Photonics (SPIE), 9, April, 2017.

Abstract
The Internet of Things envisions a web-connected infrastructure of billions of sensors and actuation devices. However, the current state-of-the-art presents another reality: monolithic end-to-end applications tightly coupled to a limited set of sensors and actuators. Growing such applications with new devices or behaviors, or extending the existing infrastructure with new applications, involves redesign and redeployment. We instead propose a modular approach to these applications, breaking them into an equivalent set of functional units (context engines) whose input/output transformations are driven by general-purpose machine learning, demonstrating an improvement in compute redundancy and computational complexity with minimal impact on accuracy. In conjunction with formal data specifications, or ontologies, we can replace application-specific implementations with a composition of context engines that use common statistical learning to generate output, thus improving context reuse. We implement interconnected context-aware applications using our approach, extracting user context from sensors in both healthcare and grid applications. We compare our infrastructure to single-stage monolithic implementations with single-point communications between sensor nodes and the cloud servers, demonstrating a reduction in combined system energy by 22-45%, and multiplying the battery lifetime of power-constrained devices by at least 22x, with easy deployment across different architectures and devices.

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Citation formats

• HTML

  Christine Chan, Michael Ostertag, Alper Sinan Akyurek,
  Tajana Simunic Rosing. <a
  href="http://www.terraswarm.org/pubs/950.html"
  >Context Aware System Design</a>, SPIE Defense and
  Security, International Society for Optics and Photonics
  (SPIE), 9, April, 2017.

• Plain text

  Christine Chan, Michael Ostertag, Alper Sinan Akyurek,
  Tajana Simunic Rosing. "Context Aware System
  Design". SPIE Defense and Security, International
  Society for Optics and Photonics (SPIE), 9, April, 2017.

• BibTeX

  @inproceedings{ChanOstertagAkyurekRosing17_ContextAwareSystemDesign,
      author = {Christine Chan and Michael Ostertag and Alper
                Sinan Akyurek and Tajana Simunic Rosing},
      title = {Context Aware System Design},
      booktitle = {SPIE Defense and Security},
      organization = {International Society for Optics and Photonics
                (SPIE)},
      day = {9},
      month = {April},
      year = {2017},
      abstract = {The Internet of Things envisions a web-connected
                infrastructure of billions of sensors and
                actuation devices. However, the current
                state-of-the-art presents another reality:
                monolithic end-to-end applications tightly coupled
                to a limited set of sensors and actuators. Growing
                such applications with new devices or behaviors,
                or extending the existing infrastructure with new
                applications, involves redesign and redeployment.
                We instead propose a modular approach to these
                applications, breaking them into an equivalent set
                of functional units (context engines) whose
                input/output transformations are driven by
                general-purpose machine learning, demonstrating an
                improvement in compute redundancy and
                computational complexity with minimal impact on
                accuracy. In conjunction with formal data
                specifications, or ontologies, we can replace
                application-specific implementations with a
                composition of context engines that use common
                statistical learning to generate output, thus
                improving context reuse. We implement
                interconnected context-aware applications using
                our approach, extracting user context from sensors
                in both healthcare and grid applications. We
                compare our infrastructure to single-stage
                monolithic implementations with single-point
                communications between sensor nodes and the cloud
                servers, demonstrating a reduction in combined
                system energy by 22-45%, and multiplying the
                battery lifetime of power-constrained devices by
                at least 22x, with easy deployment across
                different architectures and devices. },
      URL = {http://terraswarm.org/pubs/950.html}
  }
  

Posted by Christine Chan on 17 May 2017.