Task scheduling to constrain peak current consumption in wearable healthcare sensors

Sherratt, S. R. ORCID: https://orcid.org/0000-0001-7899-4445, Janko, B., Hui, T., Harwin, W. S. ORCID: https://orcid.org/0000-0002-3928-3381, Dey, N., Díaz-Sánchez, D., Wang, J. and Shi, F. (2019) Task scheduling to constrain peak current consumption in wearable healthcare sensors. Electronics, 8 (7). 789. ISSN 2079-9292 doi: 10.3390/electronics8070789 (Special Issue: Low-power Wearable Healthcare Sensors)

Abstract/Summary

Small embedded systems, in our case wearable healthcare devices, have significant engineering challenges to reduce their power consumption for longer battery life while at the same time supporting ever increasing processing requirements for more intelligent applications. Research has primarily focused on achieving lower power operation through hardware designs and intelligent methods of scheduling software tasks, all with the objective to minimize the overall consumed electrical power. However, such an approach inevitably creates points in time where software tasks and peripherals coincide to draw large peaks electrical current creating short-term electrical stress for the battery and power regulators, and adding to electromagnetic interference emissions. This position paper proposes that the power profile of an embedded device using a Real-Time Operating System (RTOS) will significantly benefit if the task scheduler is modified to be informed of the electrical current profile required for each task. This enables the task scheduler to schedule tasks that require large amounts of current to be spread over time, thus constraining the peak current that the system will draw. We propose a solution to inform the task scheduler of a tasks’ power profile and we discuss our application scenario that clearly benefited from the proposal.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/84985
Identification Number/DOI	10.3390/electronics8070789
Refereed	Yes
Divisions	Life Sciences > School of Biological Sciences > Biomedical Sciences Life Sciences > School of Biological Sciences > Department of Bio-Engineering
Publisher	MDPI
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