Citation:
Sherratt, R. S., Janko, B., Hui, T., Harwin, W. S., Dey, N., Díaz-Sánchez, D., Wang, J., Shi, F. (2019). Task Scheduling to Constrain Peak Current Consumption in Wearable Healthcare Sensors. Electronics, 8(7), 789
xmlui.dri2xhtml.METS-1.0.item-contributor-funder:
Engineering and Physical Sciences Research Council (EPSRC)
Sponsor:
This research was partially funded by the UK Engineering and Physical Sciences Research Council
(EPSRC), grant number EP/K031910/1, and in part by the Royal Society and National Natural Science Foundation
of China International Exchanges 2017 Cost Share (China), grant number IECnNSFCn170363.
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 aSmall 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 of minimizing the overall consumed electrical power. However, such an approach inevitably creates points in time where software tasks and peripherals coincide to draw large peaks of 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, which clearly benefited from the proposal[+][-]