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Hibernus++: a self-calibrating and adaptive system for transiently-powered embedded devices

Balsamo, Domenico, Weddell, Alex S., Das, Anup, Rodriguez Arreola, Alberto, Brunelli, Davide, Al-Hashimi, Bashir M., Merrett, Geoff V. and Benini, Luca (2016) Hibernus++: a self-calibrating and adaptive system for transiently-powered embedded devices IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 35, (12), pp. 1968-1980. (doi:10.1109/TCAD.2016.2547919).

Record type: Article


Energy harvesters are being used to power autonomous systems, but their output power is variable and intermittent. To sustain computation, these systems integrate batteries or supercapacitors to smooth out rapid changes in harvester output. Energy storage devices require time for charging and increase the size, mass and cost of systems. The field of transient computing moves away from this approach, by powering the system directly from the harvester output. To prevent an application from having to restart computation after a power outage, approaches such as Hibernus allow these systems to hibernate when supply failure is imminent. When the supply reaches the operating threshold, the last saved state is restored and the operation is continued from the point it was interrupted. This work proposes Hibernus++ to intelligently adapt the hibernate and restore thresholds in response to source dynamics and system load properties. Specifically, capabilities are built into the system to autonomously characterize the hardware platform and its performance during hibernation in order to set the hibernation threshold at a point which minimizes wasted energy and maximizes computation time. Similarly, the system auto-calibrates the restore threshold depending on the balance of energy supply and consumption in order to maximize computation time. Hibernus++ is validated both theoretically and experimentally on microcontroller hardware using both synthesized and real energy harvesters. Results show that Hibernus++ provides an average 16% reduction in energy consumption and an improvement of 17% in application execution time over stateof- the-art approaches.

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Accepted/In Press date: 10 March 2016
e-pub ahead of print date: 29 March 2016
Published date: December 2016
Additional Information: (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Organisations: Electronics & Computer Science


Local EPrints ID: 390250
PURE UUID: 902513fc-46dd-44af-bb57-48dd52ea3f89
ORCID for Alex S. Weddell: ORCID iD
ORCID for Geoff V. Merrett: ORCID iD

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Date deposited: 23 Mar 2016 11:17
Last modified: 03 Oct 2017 16:38

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Author: Domenico Balsamo
Author: Alex S. Weddell ORCID iD
Author: Anup Das
Author: Alberto Rodriguez Arreola
Author: Davide Brunelli
Author: Geoff V. Merrett ORCID iD
Author: Luca Benini

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