A Data-driven Synchronization Technique for Cyber-Physical Systems
Terrell R. Bennett, Nicholas Gans, Roozbeh Jafari

Citation
Terrell R. Bennett, Nicholas Gans, Roozbeh Jafari. "A Data-driven Synchronization Technique for Cyber-Physical Systems". Second International Workshop on the Swarm at the Edge of the Cloud (SWEC), in conjunction with CPSWeek, Seattle., 13, April, 2015.

Abstract
In this paper, we present a method to synchronize data from multiple sensors in a cyber-physical system without any software or hardware modifications to the sensors. This method allows for synchronization of low-power embedded systems in heterogeneous sensor networks, regardless of accuracy of individual sensor clocks by using the events in the physical world to drive the synchronization in the cyber world. We propose two methods to select portions of sensor data streams to drive the synchronization: one leveraging the notion of known templates and the other using an information theoretic approach. Using the events as well as cues from the delay models, we determine alignment points between the data streams. These alignment points are used to synchronize the data. This novel approach is based solely on the sensor data for synchronization, and it can be applied post-deployment on systems of heterogeneous sensors that are not well designed and lack effective synchronization. Experiments show an average accuracy improvement from ~12000ppm to ~2400ppm for a template-based method and from ~12000 to ~277ppm and ~445ppm for information theoretic methods when comparing the synchronized (corrected) clock data to an ideal clock source.

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Citation formats

• HTML

  Terrell R. Bennett, Nicholas Gans, Roozbeh Jafari. <a
  href="http://www.terraswarm.org/pubs/513.html"
  >A Data-driven Synchronization Technique for
  Cyber-Physical Systems</a>, Second International
  Workshop on the Swarm at the Edge of the Cloud (SWEC), in
  conjunction with CPSWeek, Seattle., 13, April, 2015.

• Plain text

  Terrell R. Bennett, Nicholas Gans, Roozbeh Jafari. "A
  Data-driven Synchronization Technique for Cyber-Physical
  Systems". Second International Workshop on the Swarm at
  the Edge of the Cloud (SWEC), in conjunction with CPSWeek,
  Seattle., 13, April, 2015.

• BibTeX

  @inproceedings{BennettGansJafari15_DatadrivenSynchronizationTechniqueForCyberPhysical,
      author = {Terrell R. Bennett and Nicholas Gans and Roozbeh
                Jafari},
      title = {A Data-driven Synchronization Technique for
                Cyber-Physical Systems},
      booktitle = {Second International Workshop on the Swarm at the
                Edge of the Cloud (SWEC), in conjunction with
                CPSWeek, Seattle.},
      day = {13},
      month = {April},
      year = {2015},
      abstract = {In this paper, we present a method to synchronize
                data from multiple sensors in a cyber-physical
                system without any software or hardware
                modifications to the sensors. This method allows
                for synchronization of low-power embedded systems
                in heterogeneous sensor networks, regardless of
                accuracy of individual sensor clocks by using the
                events in the physical world to drive the
                synchronization in the cyber world. We propose two
                methods to select portions of sensor data streams
                to drive the synchronization: one leveraging the
                notion of known templates and the other using an
                information theoretic approach. Using the events
                as well as cues from the delay models, we
                determine alignment points between the data
                streams. These alignment points are used to
                synchronize the data. This novel approach is based
                solely on the sensor data for synchronization, and
                it can be applied post-deployment on systems of
                heterogeneous sensors that are not well designed
                and lack effective synchronization. Experiments
                show an average accuracy improvement from
                ~12000ppm to ~2400ppm for a template-based method
                and from ~12000 to ~277ppm and ~445ppm for
                information theoretic methods when comparing the
                synchronized (corrected) clock data to an ideal
                clock source. },
      URL = {http://terraswarm.org/pubs/513.html}
  }
  

Posted by Christopher Brooks on 5 Mar 2015.