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Energy-Driven Computing: Rethinking the Design of Energy Harvesting Systems

Energy-Driven Computing: Rethinking the Design of Energy Harvesting Systems
Energy-Driven Computing: Rethinking the Design of Energy Harvesting Systems
Energy harvesting computing has been gaining increasing traction over the past decade, fueled by technological developments and rising demand for autonomous and battery-free systems. Energy harvesting introduces numerous challenges to embedded systems but, arguably the greatest, is the required transition from an energy source that typically provides virtually unlimited power for a reasonable period of time until it becomes exhausted, to a power source that is highly unpredictable and dynamic (both spatially and temporally, and with a range spanning many orders of magnitude). The typical approach to overcome this is the addition of intermediate energy storage/buffering to smooth out the temporal dynamics of both power supply and consumption. This has the advantage that, if correctly sized, the system ‘looks like’ a battery-powered system; however, it also adds volume, mass, cost and complexity and, if not sized correctly, unreliability. In this paper, we consider energy-driven computing, where systems are designed from the outset to operate from an energy harvesting source. Such systems typically contain little or no additional energy storage (instead relying on tiny parasitic and decoupling capacitance), alleviating the aforementioned issues. Examples of energy-driven computing include transient systems (which power down when the supply disappears and efficiently continue execution when it returns) and power-neutral systems (which operate directly from the instantaneous power harvested, gracefully modulating their consumption and performance to match the supply). In this paper, we introduce a taxonomy of energy-driven computing, articulating how power-neutral, transient, and energy-driven systems present a different class of computing to conventional approaches.
power neutral, transient computing, energy harvesting, battery-free computing, energy-driven computing
IEEE
Merrett, Geoff V
89b3a696-41de-44c3-89aa-b0aa29f54020
Al-Hashimi, Bashir B M
0b29c671-a6d2-459c-af68-c4614dce3b5d
Merrett, Geoff V
89b3a696-41de-44c3-89aa-b0aa29f54020
Al-Hashimi, Bashir B M
0b29c671-a6d2-459c-af68-c4614dce3b5d

Merrett, Geoff V and Al-Hashimi, Bashir B M (2017) Energy-Driven Computing: Rethinking the Design of Energy Harvesting Systems. In Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017. IEEE. 6 pp . (doi:10.23919/DATE.2017.7927130).

Record type: Conference or Workshop Item (Paper)

Abstract

Energy harvesting computing has been gaining increasing traction over the past decade, fueled by technological developments and rising demand for autonomous and battery-free systems. Energy harvesting introduces numerous challenges to embedded systems but, arguably the greatest, is the required transition from an energy source that typically provides virtually unlimited power for a reasonable period of time until it becomes exhausted, to a power source that is highly unpredictable and dynamic (both spatially and temporally, and with a range spanning many orders of magnitude). The typical approach to overcome this is the addition of intermediate energy storage/buffering to smooth out the temporal dynamics of both power supply and consumption. This has the advantage that, if correctly sized, the system ‘looks like’ a battery-powered system; however, it also adds volume, mass, cost and complexity and, if not sized correctly, unreliability. In this paper, we consider energy-driven computing, where systems are designed from the outset to operate from an energy harvesting source. Such systems typically contain little or no additional energy storage (instead relying on tiny parasitic and decoupling capacitance), alleviating the aforementioned issues. Examples of energy-driven computing include transient systems (which power down when the supply disappears and efficiently continue execution when it returns) and power-neutral systems (which operate directly from the instantaneous power harvested, gracefully modulating their consumption and performance to match the supply). In this paper, we introduce a taxonomy of energy-driven computing, articulating how power-neutral, transient, and energy-driven systems present a different class of computing to conventional approaches.

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Accepted/In Press date: 14 November 2016
e-pub ahead of print date: 27 March 2017
Published date: 5 May 2017
Venue - Dates: Conference on Design, Automation and Test in Europe 2017 (DATE'17), Swisstech, Lausanne, Switzerland, 2017-03-27 - 2017-03-31
Keywords: power neutral, transient computing, energy harvesting, battery-free computing, energy-driven computing
Organisations: Electronic & Software Systems

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Local EPrints ID: 404363
URI: http://eprints.soton.ac.uk/id/eprint/404363
PURE UUID: 43a85cbb-8bbf-45b3-b205-373f768119df
ORCID for Geoff V Merrett: ORCID iD orcid.org/0000-0003-4980-3894

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Date deposited: 10 Jan 2017 11:20
Last modified: 16 Mar 2024 03:46

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Contributors

Author: Geoff V Merrett ORCID iD
Author: Bashir B M Al-Hashimi

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