@scale: insights from a large, long-lived appliance energy WSN

  • Authors:

  • Stephen Dawson-Haggerty;Steven Lanzisera;Jay Taneja;Richard Brown;David Culler

  • Affiliations:

  • University of California, Berkeley, Berkeley, CA, USA;Lawrence Berkeley National Lab, Berkeley, CA, USA;University of California, Berkeley, Berkeley, CA, USA;Lawrence Berkeley National Lab, Berkeley, CA, USA;University of California, Berkeley, Berkeley, CA, USA

  • Venue:
  • Proceedings of the 11th international conference on Information Processing in Sensor Networks
  • Year:
  • 2012

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Abstract

We present insights obtained from conducting a year-long, 455 meter deployment of wireless plug-load electric meters in a large commercial building. We develop a stratified sampling methodology for surveying the energy use of Miscellaneous Electric Loads (MELs) in commercial buildings, and apply it to our study building. Over the deployment period, we collected over nine hundred million individual readings. Among our findings, we document the need for a dynamic, scalable IPv6 routing protocol which supports point-to-point routing and multiple points of egress. Although the meters are static physically, we find that the set of links they use is dynamic; not using such a dynamic set results in paths that are twice as long. Finally, we conduct a detailed survey of the accuracy possible with inexpensive AC metering hardware. Based on a 21-point automated calibration of a population of 500 devices, we find that it is possible to produce nearly utility-grade metering data.