Near-optimal energy allocation for self-powered wearable systems

Ganapati Bhat, Jaehyun Park, Umit Ogras

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

Wearable internet of things (IoT) devices are becoming popular due to their small form factor and low cost. Potential applications include human health and activity monitoring by embedding sensors such as accelerometer, gyroscope, and heart rate sensor. However, these devices have severely limited battery capacity, which requires frequent recharging. Harvesting ambient energy and optimal energy allocation can make wearable IoT devices practical by eliminating the charging requirement. This paper presents a near-optimal runtime energy management technique by considering the harvested energy. The proposed solution maximizes the performance of the wearable device under minimum energy constraints. We show that the results of the proposed algorithm are, on average, within 3% of the optimal solution computed offline.

Original languageEnglish (US)
Title of host publication2017 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages368-375
Number of pages8
Volume2017-November
ISBN (Electronic)9781538630938
DOIs
StatePublished - Dec 13 2017
Event36th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2017 - Irvine, United States
Duration: Nov 13 2017Nov 16 2017

Other

Other36th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2017
CountryUnited States
CityIrvine
Period11/13/1711/16/17

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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  • Cite this

    Bhat, G., Park, J., & Ogras, U. (2017). Near-optimal energy allocation for self-powered wearable systems. In 2017 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2017 (Vol. 2017-November, pp. 368-375). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCAD.2017.8203801