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Exploring the effect of energy storage sizing on intermittent computing system performance

Exploring the effect of energy storage sizing on intermittent computing system performance
Exploring the effect of energy storage sizing on intermittent computing system performance
Batteryless energy-harvesting devices promise to deliver a sustainable Internet of Things. Intermittent computing is an emerging area, where application forward progress, i.e. computation beneficial to the progress of the active application, is maintained by saving volatile computing state into non-volatile memory before power interruptions, and restored afterwards. Conventional intermittent computing approaches typically minimize energy storage to reduce device dimensions and interruption periods, but this can result in high state-saving and -restoring overheads and impede forward progress. In this paper, we argue that adding a small amount of energy storage can significantly improve forward progress. We develop an intermittent computing model that accurately estimates forward progress, with an experimentally validated mean error of 0.5%. Using this model, we show that sizing energy storage can improve forward progress by up to 65% with a constant current supply, and 43% with real-world photovoltaic sources. An extension to this approach, which uses a cost function to trade-off the energy storage size against forward progress, can save 83% of capacitor volume and 91% of interruption periods while maintaining 93% of the maximum forward progress.
intermittent computing, energy harvesting, energy storage, forward progress, batteryless, internet of things
0278-0070
Zhan, Jie
f9606cb9-4a11-4191-9ee4-3aabc524482b
Merrett, Geoff
89b3a696-41de-44c3-89aa-b0aa29f54020
Weddell, Alexander
3d8c4d63-19b1-4072-a779-84d487fd6f03
Zhan, Jie
f9606cb9-4a11-4191-9ee4-3aabc524482b
Merrett, Geoff
89b3a696-41de-44c3-89aa-b0aa29f54020
Weddell, Alexander
3d8c4d63-19b1-4072-a779-84d487fd6f03

Zhan, Jie, Merrett, Geoff and Weddell, Alexander (2021) Exploring the effect of energy storage sizing on intermittent computing system performance. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. (In Press)

Record type: Article

Abstract

Batteryless energy-harvesting devices promise to deliver a sustainable Internet of Things. Intermittent computing is an emerging area, where application forward progress, i.e. computation beneficial to the progress of the active application, is maintained by saving volatile computing state into non-volatile memory before power interruptions, and restored afterwards. Conventional intermittent computing approaches typically minimize energy storage to reduce device dimensions and interruption periods, but this can result in high state-saving and -restoring overheads and impede forward progress. In this paper, we argue that adding a small amount of energy storage can significantly improve forward progress. We develop an intermittent computing model that accurately estimates forward progress, with an experimentally validated mean error of 0.5%. Using this model, we show that sizing energy storage can improve forward progress by up to 65% with a constant current supply, and 43% with real-world photovoltaic sources. An extension to this approach, which uses a cost function to trade-off the energy storage size against forward progress, can save 83% of capacitor volume and 91% of interruption periods while maintaining 93% of the maximum forward progress.

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Accepted/In Press date: 8 March 2021
Keywords: intermittent computing, energy harvesting, energy storage, forward progress, batteryless, internet of things

Identifiers

Local EPrints ID: 448014
URI: http://eprints.soton.ac.uk/id/eprint/448014
ISSN: 0278-0070
PURE UUID: 3363d2e8-b73e-46d9-b889-4579f3cea84a
ORCID for Jie Zhan: ORCID iD orcid.org/0000-0002-9196-757X
ORCID for Geoff Merrett: ORCID iD orcid.org/0000-0003-4980-3894
ORCID for Alexander Weddell: ORCID iD orcid.org/0000-0002-6763-5460

Catalogue record

Date deposited: 30 Mar 2021 16:33
Last modified: 13 Apr 2021 01:56

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