Abstract
Energy efficiency is highly desirable for sensing systems in the Internet of Things. A common approach to achieve low-power systems is duty cycling, where components in a system are turned OFF periodically to meet an energy budget. However, this paper shows that such an approach is not necessarily optimal in energy efficiency, and proposes guided processing as a fundamentally better alternative. The proposed approach offers: 1) explicit modeling of performance uncertainties in system internals; 2) a realistic resource consumption model; and 3) a key insight into the superiority of guided processing over duty cycling. Generalization from the cascade structure to the more general graph-based one is also presented. Once applied to optimize a large-scale audio sensing system with a practical detection application, empirical results show that the proposed approach significantly improves the detection performance (up to 1.7 times and 4 times reduction in false alarm and miss rate, respectively) for the same energy consumption, when compared with the duty-cycling approach.
| Original language | English (US) |
|---|---|
| Article number | 7924310 |
| Pages (from-to) | 2414-2426 |
| Number of pages | 13 |
| Journal | IEEE Transactions on Circuits and Systems I: Regular Papers |
| Volume | 64 |
| Issue number | 9 |
| DOIs | |
| State | Published - Sep 2017 |
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Keywords
- Guided-processing
- IoT
- duty-cycling
- energy-efficient systems
- resource-aware optimization
ASJC Scopus subject areas
- Electrical and Electronic Engineering
Cite this
Guided-Processing Outperforms Duty-Cycling for Energy-Efficient Systems. / Le, Long N.; Jones, Douglas L.
In: IEEE Transactions on Circuits and Systems I: Regular Papers, Vol. 64, No. 9, 7924310, 09.2017, p. 2414-2426.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Guided-Processing Outperforms Duty-Cycling for Energy-Efficient Systems
AU - Le, Long N.
AU - Jones, Douglas L
PY - 2017/9
Y1 - 2017/9
N2 - Energy efficiency is highly desirable for sensing systems in the Internet of Things. A common approach to achieve low-power systems is duty cycling, where components in a system are turned OFF periodically to meet an energy budget. However, this paper shows that such an approach is not necessarily optimal in energy efficiency, and proposes guided processing as a fundamentally better alternative. The proposed approach offers: 1) explicit modeling of performance uncertainties in system internals; 2) a realistic resource consumption model; and 3) a key insight into the superiority of guided processing over duty cycling. Generalization from the cascade structure to the more general graph-based one is also presented. Once applied to optimize a large-scale audio sensing system with a practical detection application, empirical results show that the proposed approach significantly improves the detection performance (up to 1.7 times and 4 times reduction in false alarm and miss rate, respectively) for the same energy consumption, when compared with the duty-cycling approach.
AB - Energy efficiency is highly desirable for sensing systems in the Internet of Things. A common approach to achieve low-power systems is duty cycling, where components in a system are turned OFF periodically to meet an energy budget. However, this paper shows that such an approach is not necessarily optimal in energy efficiency, and proposes guided processing as a fundamentally better alternative. The proposed approach offers: 1) explicit modeling of performance uncertainties in system internals; 2) a realistic resource consumption model; and 3) a key insight into the superiority of guided processing over duty cycling. Generalization from the cascade structure to the more general graph-based one is also presented. Once applied to optimize a large-scale audio sensing system with a practical detection application, empirical results show that the proposed approach significantly improves the detection performance (up to 1.7 times and 4 times reduction in false alarm and miss rate, respectively) for the same energy consumption, when compared with the duty-cycling approach.
KW - Guided-processing
KW - IoT
KW - duty-cycling
KW - energy-efficient systems
KW - resource-aware optimization
UR - http://www.scopus.com/inward/record.url?scp=85018860117&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85018860117&partnerID=8YFLogxK
U2 - 10.1109/TCSI.2017.2690909
DO - 10.1109/TCSI.2017.2690909
M3 - Article
AN - SCOPUS:85018860117
VL - 64
SP - 2414
EP - 2426
JO - IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
JF - IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
SN - 1549-8328
IS - 9
M1 - 7924310
ER -