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An efficient tinification of the linux kernel for minimizing resource consumption

Authors:

Takuya Shizukuishi,

Katsuya MatsubaraAuthors Info & Claims

SAC '20: Proceedings of the 35th Annual ACM Symposium on Applied Computing

Pages 1228 - 1237

https://doi.org/10.1145/3341105.3373913

Published: 30 March 2020 Publication History

Abstract

Reusable libraries and rich functional operating systems (OSs) have been significantly improving system development in terms of time-to-market and product quality. On the other hand, such general-purpose software often has code and data that is useless for the target system. Therefore, an optimization mechanism must be developed to efficiently extract only the necessary and sufficient functions from the whole software code.

This study aims to support optimizing Linux, which is the most used OS in various systems, including embedded devices. Embedded devices may especially require Linux to be optimized because of limited computing resources and costs. Linux Kernel Config allows unnecessary functions to be removed explicitly during system building. Nevertheless, an optimal configuration setting is hard to specify manually for each target system because there are about 10,000 selectable config options in the Linux Kernel Config. We propose a method to automatically estimate the effect on the memory usage and power consumption of each Kernel Config option in a target system. Results of an experiment show our method makes it possible to automatically specify config options that could be disabled to effectively shrink resource usage for a target system.

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Cited By

Singh YSingh A(2022)Retracted: Minimizing Memory Usage for Resource Constrained Devices using Deep Convolutional Neural Networks2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon)10.1109/MysuruCon55714.2022.9972384(1-6)Online publication date: 16-Oct-2022
https://doi.org/10.1109/MysuruCon55714.2022.9972384
Lambert JMonahan RCasey K(2021)Power Consumption Profiling of a Lightweight Development Board: Sensing with the INA219 and Teensy 4.0 MicrocontrollerElectronics10.3390/electronics1007077510:7(775)Online publication date: 25-Mar-2021
https://doi.org/10.3390/electronics10070775
Shizukuishi TMatsubara K(2021)Efficient Tailoring of Universal Software Components for Conserving Resources: Evaluation in Practical ROS-based System2021 IEEE/SICE International Symposium on System Integration (SII)10.1109/IEEECONF49454.2021.9382728(431-436)Online publication date: 11-Jan-2021
https://doi.org/10.1109/IEEECONF49454.2021.9382728

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An efficient tinification of the linux kernel for minimizing resource consumption

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Information

Published In

cover image ACM Conferences

SAC '20: Proceedings of the 35th Annual ACM Symposium on Applied Computing

March 2020

2348 pages

ISBN:9781450368667

DOI:10.1145/3341105

Conference Chairs:
Chih-Cheng Hung
Kennesaw State University
,
Tomas Cerny
Baylor University
,
Program Chairs:
Dongwan Shin
New Mexico Tech
,
Alessio Bechini
University of Pisa, Italy

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGAPP: ACM Special Interest Group on Applied Computing

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 March 2020

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SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing

March 30 - April 3, 2020

Brno, Czech Republic

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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The 40th ACM/SIGAPP Symposium on Applied Computing

March 31 - April 4, 2025

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Cited By

Singh YSingh A(2022)Retracted: Minimizing Memory Usage for Resource Constrained Devices using Deep Convolutional Neural Networks2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon)10.1109/MysuruCon55714.2022.9972384(1-6)Online publication date: 16-Oct-2022
https://doi.org/10.1109/MysuruCon55714.2022.9972384
Lambert JMonahan RCasey K(2021)Power Consumption Profiling of a Lightweight Development Board: Sensing with the INA219 and Teensy 4.0 MicrocontrollerElectronics10.3390/electronics1007077510:7(775)Online publication date: 25-Mar-2021
https://doi.org/10.3390/electronics10070775
Shizukuishi TMatsubara K(2021)Efficient Tailoring of Universal Software Components for Conserving Resources: Evaluation in Practical ROS-based System2021 IEEE/SICE International Symposium on System Integration (SII)10.1109/IEEECONF49454.2021.9382728(431-436)Online publication date: 11-Jan-2021
https://doi.org/10.1109/IEEECONF49454.2021.9382728

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