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).


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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.

Item Type: Article
Digital Object Identifier (DOI): doi:10.1109/TCAD.2016.2547919
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.
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Organisations: Electronics & Computer Science
ePrint ID: 390250
Date :
Date Event
10 March 2016Accepted/In Press
29 March 2016e-pub ahead of print
December 2016Published
Date Deposited: 23 Mar 2016 11:17
Last Modified: 17 Apr 2017 03:52
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/390250

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