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An ultra low-power processor for sensor networks
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Source Architectural Support for Programming Languages and Operating Systems archive
Proceedings of the 11th international conference on Architectural support for programming languages and operating systems table of contents
Boston, MA, USA
SESSION: New models and architectures table of contents
Pages: 27 - 36  
Year of Publication: 2004
ISBN:1-58113-804-0
Also published in ...
Authors
Virantha Ekanayake  Cornell University, Ithaca, NY
Clinton Kelly, IV  Cornell University, Ithaca, NY
Rajit Manohar  Cornell University, Ithaca, NY
Sponsors
SIGPLAN: ACM Special Interest Group on Programming Languages
SIGOPS: ACM Special Interest Group on Operating Systems
SIGARCH: ACM Special Interest Group on Computer Architecture
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

We present a novel processor architecture designed specifically for use in low-power wireless sensor-network nodes. Our sensor network asynchronous processor (SNAP/LE) is based on an asynchronous data-driven 16-bit RISC core with an extremely low-power idle state, and a wakeup response latency on the order of tens of nanoseconds. The processor instruction set is optimized for sensor-network applications, with support for event scheduling, pseudo-random number generation, bitfield operations, and radio/sensor interfaces. SNAP/LE has a hardware event queue and event coprocessors, which allow the processor to avoid the overhead of operating system software (such as task schedulers and external interrupt servicing), while still providing a straightforward programming interface to the designer. The processor can meet performance levels required for data monitoring applications while executing instructions with tens of picojoules of energy.We evaluate the energy consumption of SNAP/LE with several applications representative of the workload found in data-gathering wireless sensor networks. We compare our architecture and software against existing platforms for sensor networks, quantifying both the software and hardware benefits of our approach.


REFERENCES

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CITED BY  8
 

Collaborative Colleagues:
Virantha Ekanayake: colleagues
Clinton Kelly, IV: colleagues
Rajit Manohar: colleagues