The Tenet architecture for tiered sensor networks

  • Authors:

  • Jeongyeup Paek;Ben Greenstein;Omprakash Gnawali;Ki-Young Jang;August Joki;Marcos Vieira;John Hicks;Deborah Estrin;Ramesh Govindan;Eddie Kohler

  • Affiliations:

  • University of Southern California, Los Angeles, CA;Intel Labs Seattle, Seattle, WA;Stanford University, Stanford, CA;University of Southern California, Los Angeles, CA;University of California, Los Angeles, CA;University of Southern California, Los Angeles, CA;University of California, Los Angeles, CA;University of California, Los Angeles, CA;University of Southern California, Los Angeles, CA;University of California, Los Angeles, CA

  • Venue:
  • ACM Transactions on Sensor Networks (TOSN)
  • Year:
  • 2010

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Abstract

Most sensor network research and software design has been guided by an architectural principle that permits multinode data fusion on small-form-factor, resource-poor nodes, or motes. While we were among the earliest promoters of this approach, through experience we found that this principle leads to fragile and unmanageable systems and explore an alternative. The Tenet architecture is motivated by the observation that future large-scale sensor network deployments will be tiered, consisting of motes in the lower tier and masters, relatively unconstrained 32-bit platform nodes, in the upper tier. Tenet constrains multinode fusion to the master tier while allowing motes to process locally-generated sensor data. This simplifies application development and allows mote-tier software to be reused. Applications running on masters task motes by composing task descriptions from a novel tasklet library. Our Tenet implementation also contains a robust and scalable networking subsystem for disseminating tasks and reliably delivering responses. We show that a Tenet pursuit-evasion application exhibits performance comparable to a mote-native implementation while being considerably more compact. We also present two real-world deployments of Tenet system: a structural vibration monitoring application at Vincent Thomas Bridge and an imaging-based habitat monitoring application at James Reserve, and show that tiered architecture scales network capacity and allows reliable delivery of high rate data.1