Voltage-Frequency Domain Optimization for Energy-Neutral Wearable Health Devices
Wearable health and activity monitoring devices must minimize the battery charging and replacement requirements to be practical. Numerous design techniques, such as power gating and multiple voltage-frequency (VF) domains, can be used to optimize power consumption. However, circuit-level techniques...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/18/5255 |
| _version_ | 1827706259864813568 |
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| author | Yigit Tuncel Sizhe An Ganapati Bhat Naga Raja Hyung Gyu Lee Umit Ogras |
| author_facet | Yigit Tuncel Sizhe An Ganapati Bhat Naga Raja Hyung Gyu Lee Umit Ogras |
| author_sort | Yigit Tuncel |
| collection | DOAJ |
| description | Wearable health and activity monitoring devices must minimize the battery charging and replacement requirements to be practical. Numerous design techniques, such as power gating and multiple voltage-frequency (VF) domains, can be used to optimize power consumption. However, circuit-level techniques alone cannot minimize energy consumption unless they exploit domain-specific knowledge. To this end, we propose a system-level framework that minimizes the energy consumption of wearable health and activity monitoring applications by combining domain-specific knowledge with low-power design techniques. The proposed technique finds the energy-optimal VF domain partitioning and the corresponding VF assignments to each partition. We evaluate this framework with experiments on two activity monitoring and one electrocardiogram applications. Our approach decreases the energy consumption by 33–58% when compared to baseline designs. It also achieves 20–46% more savings compared to a state-of-the-art approach. |
| first_indexed | 2024-03-10T16:21:01Z |
| format | Article |
| id | doaj.art-e34ae6ed6f60400aacf2d37971174e97 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T16:21:01Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e34ae6ed6f60400aacf2d37971174e972023-11-20T13:43:25ZengMDPI AGSensors1424-82202020-09-012018525510.3390/s20185255Voltage-Frequency Domain Optimization for Energy-Neutral Wearable Health DevicesYigit Tuncel0Sizhe An1Ganapati Bhat2Naga Raja3Hyung Gyu Lee4Umit Ogras5Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USADepartment of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USASchool of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164, USASchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287, USASchool of Computer and Communication Engineering, Daegu University, Gyeongsan 38453, KoreaDepartment of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USAWearable health and activity monitoring devices must minimize the battery charging and replacement requirements to be practical. Numerous design techniques, such as power gating and multiple voltage-frequency (VF) domains, can be used to optimize power consumption. However, circuit-level techniques alone cannot minimize energy consumption unless they exploit domain-specific knowledge. To this end, we propose a system-level framework that minimizes the energy consumption of wearable health and activity monitoring applications by combining domain-specific knowledge with low-power design techniques. The proposed technique finds the energy-optimal VF domain partitioning and the corresponding VF assignments to each partition. We evaluate this framework with experiments on two activity monitoring and one electrocardiogram applications. Our approach decreases the energy consumption by 33–58% when compared to baseline designs. It also achieves 20–46% more savings compared to a state-of-the-art approach.https://www.mdpi.com/1424-8220/20/18/5255voltage-frequency domainsoptimizationwearable deviceslow-power designenergy consumption |
| spellingShingle | Yigit Tuncel Sizhe An Ganapati Bhat Naga Raja Hyung Gyu Lee Umit Ogras Voltage-Frequency Domain Optimization for Energy-Neutral Wearable Health Devices Sensors voltage-frequency domains optimization wearable devices low-power design energy consumption |
| title | Voltage-Frequency Domain Optimization for Energy-Neutral Wearable Health Devices |
| title_full | Voltage-Frequency Domain Optimization for Energy-Neutral Wearable Health Devices |
| title_fullStr | Voltage-Frequency Domain Optimization for Energy-Neutral Wearable Health Devices |
| title_full_unstemmed | Voltage-Frequency Domain Optimization for Energy-Neutral Wearable Health Devices |
| title_short | Voltage-Frequency Domain Optimization for Energy-Neutral Wearable Health Devices |
| title_sort | voltage frequency domain optimization for energy neutral wearable health devices |
| topic | voltage-frequency domains optimization wearable devices low-power design energy consumption |
| url | https://www.mdpi.com/1424-8220/20/18/5255 |
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