Hybrid Power Failure Recovery for Intermittent Computing

Energy harvesting systems rely on either rollback or roll-forward recovery to resume power-interrupted program correctly. However, both recovery schemes have their own inherent drawbacks. To this end, this paper presents RollSwitch, a hybrid power failure recovery scheme that can achieve low-cost yet high-performance intermittent computation for energy harvesting systems. According to the underlying energy harvesting condition, RollSwitch dynamically switches between rollback and roll-forward recovery modes to maximize the performance. In particular, RollSwitch leverages the level of available energy in the capacitor as a proxy for determining the appropriate recovery mode. For this purpose, RollSwitch devises a simple capacitor energy predictor whose outcome governs the recovery mode selection in the near future. The experimental results demonstrate that RollSwitch achieves 15.0% and 19.8% performance gain on average over the state-of-art rollback and roll-forward recovery schemes, respectively.

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Publication Details

Published
2024-10-27
DOI
https://doi.org/10.1145/3676536.3676654
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.42

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article

Hybrid Power Failure Recovery for Intermittent Computing

G. Fang, Jongouk Choi, Changhee Jung
2 citations
Advanced Memory and Neural Computing
0.42
article

Hybrid Power Failure Recovery for Intermittent Computing

G. Fang, Jongouk Choi, Changhee Jung
article en
2 citations

Abstract

Energy harvesting systems rely on either rollback or roll-forward recovery to resume power-interrupted program correctly. However, both recovery schemes have their own inherent drawbacks. To this end, this paper presents RollSwitch, a hybrid power failure recovery scheme that can achieve low-cost yet high-performance intermittent computation for energy harvesting systems. According to the underlying energy harvesting condition, RollSwitch dynamically switches between rollback and roll-forward recovery modes to maximize the performance. In particular, RollSwitch leverages the level of available energy in the capacitor as a proxy for determining the appropriate recovery mode. For this purpose, RollSwitch devises a simple capacitor energy predictor whose outcome governs the recovery mode selection in the near future. The experimental results demonstrate that RollSwitch achieves 15.0% and 19.8% performance gain on average over the state-of-art rollback and roll-forward recovery schemes, respectively.

University of Central Florida (US), Purdue University West Lafayette (US)
National Science Foundation
Affordable and clean energy
Openalex Percentile: Top 35%
Advanced Memory and Neural Computing
0.42
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Hybrid Power Failure Recovery for Intermittent Computing — G. Fang, Jongouk Choi, et al. · (2024) | TGRS Research Map | TGRS