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The low power energy aware processing (LEAP)embedded networked sensor system
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Source Information Processing In Sensor Networks archive
Proceedings of the 5th international conference on Information processing in sensor networks table of contents
Nashville, Tennessee, USA
SESSION: SPOTS'06 session 4--new sensors and architectures table of contents
Pages: 449 - 457  
Year of Publication: 2006
ISBN:1-59593-334-4
Authors
Dustin McIntire  University of California, Los Angeles, Los Angeles, California
Kei Ho  University of California, Los Angeles, Los Angeles, California
Bernie Yip  University of California, Los Angeles, Los Angeles, California
Amarjeet Singh  University of California, Los Angeles, Los Angeles, California
Winston Wu  University of California, Los Angeles, Los Angeles, California
William J. Kaiser  University of California, Los Angeles, Los Angeles, California
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 12,   Downloads (12 Months): 163,   Citation Count: 7
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ABSTRACT

A broad range of embedded networked sensor (ENS) systems for critical environmental monitoring applications now require complex, high peak power dissipating sensor devices, as well as on-demand high performance computing and high bandwidth communication. Embedded computing demands for these new platforms include support for computationally intensive image and signal processing as well as optimization and statistical computing. To meet these new requirements while maintaining critical support for low energy operation, a new multiprocessor node hardware and software architecture, Low Power Energy Aware Processing (LEAP), has been developed. The LEAP architecture integrates fine-grained energy dissipation monitoring and sophisticated power control scheduling for all subsystems including sensor subsystems. This paper also describes a new distributed node testbed demonstrating that by exploiting high high energy efficiency components and enabling proper on-demand scheduling, the LEAP architecture may meet both sensing performance and energy dissipation objectives for a broad class of applications.


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  7
 
 
 

Collaborative Colleagues:
Dustin McIntire: colleagues
Kei Ho: colleagues
Bernie Yip: colleagues
Amarjeet Singh: colleagues
Winston Wu: colleagues
William J. Kaiser: colleagues