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Sensors 2017, 17(2), 310;

Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC

Tsinghua National Laboratory for Information Science and Technology, Institute of Microelectronics, Tsinghua University, Beijing 100084, China
Author to whom correspondence should be addressed.
Academic Editor: Davide Brunelli
Received: 9 January 2017 / Revised: 2 February 2017 / Accepted: 2 February 2017 / Published: 8 February 2017
(This article belongs to the Special Issue Energy Harvesting Sensors for Long Term Applications in the IoT Era)
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This paper proposes a scheduling and power management solution for energy harvesting heterogeneous multi-core WSN node SoC such that the system continues to operate perennially and uses the harvested energy efficiently. The solution consists of a heterogeneous multi-core system oriented task scheduling algorithm and a low-complexity dynamic workload scaling and configuration optimization algorithm suitable for light-weight platforms. Moreover, considering the power consumption of most WSN applications have the characteristic of data dependent behavior, we introduce branches handling mechanism into the solution as well. The experimental result shows that the proposed algorithm can operate in real-time on a lightweight embedded processor (MSP430), and that it can make a system do more valuable works and make more than 99.9% use of the power budget. View Full-Text
Keywords: task scheduling; power management; energy harvesting; WSN task scheduling; power management; energy harvesting; WSN

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Li, X.; Xie, N.; Tian, X. Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC. Sensors 2017, 17, 310.

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