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Power Neutral Performance Scaling with Intrinsic MPPT for Energy Harvesting Computing Systems

Power Neutral Performance Scaling with Intrinsic MPPT for Energy Harvesting Computing Systems
Power Neutral Performance Scaling with Intrinsic MPPT for Energy Harvesting Computing Systems
Recent research has looked to supplement or even replace the batteries in embedded computing systems with energy harvesting, where energy is derived from the device’s environment. However, such supplies are generally unpredictable and highly variable, and hence systems typically incorporate large external energy buffers (e.g. supercapacitors) to sustain computation; however, these pose environmental issues and increase system size and cost. This paper proposes Momentum, a general power-neutral methodology, with intrinsic
system-wide maximum power point tracking, that can be applied to a wide range of different computing systems, where the system dynamically scales its performance (and hence power consumption) to optimize computational progress depending on the power availability. Momentum enables the system to operate around an efficient operating voltage, maximizing forward application execution, without adding any external tracking or control units. This methodology combines at run-time 1) a hierarchical control strategy which utilizes available power management controls (such as dynamic voltage and frequency scaling, and core hot-plugging) to achieve efficient power-neutral operation, 2) a software-based maximum power point tracking scheme
(unlike existing approaches, this does not require any additional hardware), which adapts the system power consumption so that it can work at the optimal operating voltage, considering the efficiency of the entire system
rather than just the energy harvester, and 3) experimental validation on two different scales of computing system: a low power microcontroller (operating from the already-present 4.7 μF decoupling capacitance) and a multi-processor system-on-chip (operating from 15.4 mF added capacitance). Experimental results from both a controlled supply and energy harvesting source show that Momentum operates correctly on both platforms, and exhibits improvements in forward application execution of up to 11% when compared to existing power-neutral approaches, and 46% compared to existing static approaches.
Energy Harvesting, Performance Adaptation, Embedded Computing Systems, Transient Computing, Maximum Power Point Tracking, Power Neutrality
1539-9087
Balsamo, Domenico
fa2dc20a-e3da-4d74-9070-9c61c6a471ba
Fletcher, Benjamin, James
b9ee2f3f-f125-47df-a73e-e61c0404d4c9
Weddell, Alexander
3d8c4d63-19b1-4072-a779-84d487fd6f03
Karatziolas, Giorgos
67244bbb-6a86-4f07-8120-0411b424c669
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d
Merrett, Geoff
89b3a696-41de-44c3-89aa-b0aa29f54020
Balsamo, Domenico
fa2dc20a-e3da-4d74-9070-9c61c6a471ba
Fletcher, Benjamin, James
b9ee2f3f-f125-47df-a73e-e61c0404d4c9
Weddell, Alexander
3d8c4d63-19b1-4072-a779-84d487fd6f03
Karatziolas, Giorgos
67244bbb-6a86-4f07-8120-0411b424c669
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d
Merrett, Geoff
89b3a696-41de-44c3-89aa-b0aa29f54020

Balsamo, Domenico, Fletcher, Benjamin, James, Weddell, Alexander, Karatziolas, Giorgos, Al-Hashimi, Bashir and Merrett, Geoff (2018) Power Neutral Performance Scaling with Intrinsic MPPT for Energy Harvesting Computing Systems. ACM Transactions on Embedded Computing Systems. (In Press)

Record type: Article

Abstract

Recent research has looked to supplement or even replace the batteries in embedded computing systems with energy harvesting, where energy is derived from the device’s environment. However, such supplies are generally unpredictable and highly variable, and hence systems typically incorporate large external energy buffers (e.g. supercapacitors) to sustain computation; however, these pose environmental issues and increase system size and cost. This paper proposes Momentum, a general power-neutral methodology, with intrinsic
system-wide maximum power point tracking, that can be applied to a wide range of different computing systems, where the system dynamically scales its performance (and hence power consumption) to optimize computational progress depending on the power availability. Momentum enables the system to operate around an efficient operating voltage, maximizing forward application execution, without adding any external tracking or control units. This methodology combines at run-time 1) a hierarchical control strategy which utilizes available power management controls (such as dynamic voltage and frequency scaling, and core hot-plugging) to achieve efficient power-neutral operation, 2) a software-based maximum power point tracking scheme
(unlike existing approaches, this does not require any additional hardware), which adapts the system power consumption so that it can work at the optimal operating voltage, considering the efficiency of the entire system
rather than just the energy harvester, and 3) experimental validation on two different scales of computing system: a low power microcontroller (operating from the already-present 4.7 μF decoupling capacitance) and a multi-processor system-on-chip (operating from 15.4 mF added capacitance). Experimental results from both a controlled supply and energy harvesting source show that Momentum operates correctly on both platforms, and exhibits improvements in forward application execution of up to 11% when compared to existing power-neutral approaches, and 46% compared to existing static approaches.

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Accepted/In Press date: 5 October 2018
Keywords: Energy Harvesting, Performance Adaptation, Embedded Computing Systems, Transient Computing, Maximum Power Point Tracking, Power Neutrality

Identifiers

Local EPrints ID: 424986
URI: https://eprints.soton.ac.uk/id/eprint/424986
ISSN: 1539-9087
PURE UUID: d6926a66-1ee2-4d9f-92bd-fe3b4e83576c
ORCID for Benjamin, James Fletcher: ORCID iD orcid.org/0000-0002-4957-1934
ORCID for Alexander Weddell: ORCID iD orcid.org/0000-0002-6763-5460
ORCID for Geoff Merrett: ORCID iD orcid.org/0000-0003-4980-3894

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Date deposited: 09 Oct 2018 16:30
Last modified: 10 Oct 2018 00:33

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