Selective policies for efficient state retention in transiently-powered embedded systems: exploiting properties of NVM technologies
Selective policies for efficient state retention in transiently-powered embedded systems: exploiting properties of NVM technologies
Transiently-powered embedded systems are emerging to enable computation to be sustained during intermittent supply, without the need for large energy buffers such as batteries or supercapacitors. To deal with the intermittent nature of the input source, these systems save the system state (i.e. registers and main memory) to Non-Volatile Memory (NVM) before a power failure, and restore it when the power supply recovers. Existing approaches normally save the entire state of the system upon power failure, but this is both energy and time consuming. In this paper, we analyse existing approaches to identify their inefficiency when used with specific NVM technologies, and propose novel selective policies for efficiently retaining the system state by exploiting properties of different NVM technologies. These policies are based on (1) concatenating multiple images into the available NVM before erasing, and (2) efficiently selecting only the system state that has changed since last saving. The existing and proposed policies are experimentally validated on two embedded platforms featuring different NVM technologies (Flash and FRAM), depending on their characteristics, in order to identify the most energy efficient policy/platform combination. Results show a reduction in energy and time overhead of up to 90.6% for Flash memory using a novel policy, and 86.2% for FRAM, compared to the typical approach of saving the entire system state.
state retention, energy harvesting, Non-volatile memories, Transient computing
Verykios, Theodoros D.
fc203333-af9c-48e6-b7d6-f22d8cf60636
Balsamo, Domenico
fa2dc20a-e3da-4d74-9070-9c61c6a471ba
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
Verykios, Theodoros D.
fc203333-af9c-48e6-b7d6-f22d8cf60636
Balsamo, Domenico
fa2dc20a-e3da-4d74-9070-9c61c6a471ba
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
Verykios, Theodoros D., Balsamo, Domenico and Merrett, Geoff V.
(2018)
Selective policies for efficient state retention in transiently-powered embedded systems: exploiting properties of NVM technologies.
Sustainable Computing: Informatics and Systems.
(doi:10.1016/j.suscom.2018.07.003).
Abstract
Transiently-powered embedded systems are emerging to enable computation to be sustained during intermittent supply, without the need for large energy buffers such as batteries or supercapacitors. To deal with the intermittent nature of the input source, these systems save the system state (i.e. registers and main memory) to Non-Volatile Memory (NVM) before a power failure, and restore it when the power supply recovers. Existing approaches normally save the entire state of the system upon power failure, but this is both energy and time consuming. In this paper, we analyse existing approaches to identify their inefficiency when used with specific NVM technologies, and propose novel selective policies for efficiently retaining the system state by exploiting properties of different NVM technologies. These policies are based on (1) concatenating multiple images into the available NVM before erasing, and (2) efficiently selecting only the system state that has changed since last saving. The existing and proposed policies are experimentally validated on two embedded platforms featuring different NVM technologies (Flash and FRAM), depending on their characteristics, in order to identify the most energy efficient policy/platform combination. Results show a reduction in energy and time overhead of up to 90.6% for Flash memory using a novel policy, and 86.2% for FRAM, compared to the typical approach of saving the entire system state.
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More information
Accepted/In Press date: 11 July 2018
e-pub ahead of print date: 25 July 2018
Keywords:
state retention, energy harvesting, Non-volatile memories, Transient computing
Identifiers
Local EPrints ID: 422555
URI: http://eprints.soton.ac.uk/id/eprint/422555
ISSN: 2210-5379
PURE UUID: a3367573-6006-4818-bf7c-951f3e0a77c4
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Date deposited: 25 Jul 2018 16:30
Last modified: 16 Mar 2024 06:54
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Contributors
Author:
Theodoros D. Verykios
Author:
Domenico Balsamo
Author:
Geoff V. Merrett
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