“ The TENET Architecture for Tiered Sensor Networks ” by Omprakash Gnawali, Ben Greenstein, Ki-Young Jang, August Joki, Jeongyeup Paek, Marcos Vieira, Deborah Estrin, Ramesh Govindan, and Eddie Kohler. In Proceedings of the ACM Conference on Embedded Networked Sensor Systems (SenSys 2006) , November 2006.
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 largescale 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 multinode fusion to the master tier while allowing motes to process locally-generated sensor data. This simples 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.
BibTeX entry:
@inproceedings{tenetsensys2006,
author = {Omprakash Gnawali, and Ben Greenstein and Ki-Young Jang and
August Joki and Jeongyeup Paek and Marcos Vieira and Deborah
Estrin and Ramesh Govindan and Eddie Kohler},
title = { {The TENET Architecture for Tiered Sensor Networks} },
booktitle = { Proceedings of the ACM Conference on Embedded Networked
Sensor Systems (SenSys 2006) },
month = { November },
year = {2006}
}