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The Tenet architecture for tiered sensor networks
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Source Conference On Embedded Networked Sensor Systems archive
Proceedings of the 4th international conference on Embedded networked sensor systems table of contents
Boulder, Colorado, USA
SESSION: Architecture table of contents
Pages: 153 - 166  
Year of Publication: 2006
ISBN:1-59593-343-3
Authors
Omprakash Gnawali  University of Southern California
Ki-Young Jang  University of Southern California
Jeongyeup Paek  University of Southern California
Marcos Vieira  University of Southern California
Ramesh Govindan  University of Southern California
Ben Greenstein  University of California, Los Angeles
August Joki  University of California, Los Angeles
Deborah Estrin  University of California, Los Angeles
Eddie Kohler  University of California, Los Angeles
Sponsors
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
SIGCOMM: ACM Special Interest Group on Data Communication
SIGOPS: ACM Special Interest Group on Operating Systems
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
ACM: Association for Computing Machinery
SIGBED: ACM Special Interest Group on Embedded Systems
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 24,   Downloads (12 Months): 178,   Citation Count: 44
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ABSTRACT

Most sensor network research and software design has been guided by an architectural principle that permits multi-node data fusion on small-form-factor, resource-poor nodes, or motes. We argue 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. Masters provide increased network capacity. Tenet constrains multi-node 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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  44

Collaborative Colleagues:
Omprakash Gnawali: colleagues
Ki-Young Jang: colleagues
Jeongyeup Paek: colleagues
Marcos Vieira: colleagues
Ramesh Govindan: colleagues
Ben Greenstein: colleagues
August Joki: colleagues
Deborah Estrin: colleagues
Eddie Kohler: colleagues