Loading…

Performance Evaluation of Containerization Platforms for Control and Monitoring Devices

Containerization platforms such as Docker are now common practice in the IT industry and are frequently used in combination with virtual machines in cloud-scenarios. Using containerization platforms for embedded control and monitoring devices has so far been much less common. However, the advantages...

Full description

Saved in:
Bibliographic Details
Main Authors: Manninen, Harri, Jaaskelainen, Vesa, Blech, Jan Olaf
Format: Conference Proceeding
Language:English
Subjects:
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 1064
container_issue
container_start_page 1061
container_title
container_volume 1
creator Manninen, Harri
Jaaskelainen, Vesa
Blech, Jan Olaf
description Containerization platforms such as Docker are now common practice in the IT industry and are frequently used in combination with virtual machines in cloud-scenarios. Using containerization platforms for embedded control and monitoring devices has so far been much less common. However, the advantages such as increased modularization and portability are of relevance for embedded control devices as well. On the other hand, embedded control devices are often characterized by a limited amount of computational resources and may face other constraints such as requirements on low power consumption. This paper presents first steps on estimating the resource needs for different containerization platforms. We present empirical work on resource consumption of containerization platforms for a Raspberry Pi-based control and monitoring device and look at CPU load, memory usage and power consumption.
doi_str_mv 10.1109/ETFA46521.2020.9211901
format conference_proceeding
fullrecord <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_9211901</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9211901</ieee_id><sourcerecordid>9211901</sourcerecordid><originalsourceid>FETCH-LOGICAL-i251t-6737bf0c4260f298c7c1b404c7ce25de8257eb55be7202889e0e5c9891b057b03</originalsourceid><addsrcrecordid>eNotUF1LwzAUjYLgnPsFguQPtN6bNk3yOGo3hYl7mOjbSLtbiXSJpHWgv97q9nIO3PMB9zB2i5AigrmrNot5XkiBqQABqRGIBvCMXaESGrWRxds5m6DJiwSUNJds1vcfADBmC5OZCXtdU2xD3FvfEK8Otvuygwueh5aXwQ_WeYru53hbd3b48_Z8xH85ho5bv-NPwbshROff-T0dXEP9NbtobdfT7MRT9rKoNuVDsnpePpbzVeKExCEpVKbqFppcFNAKoxvVYJ1DPjIJuSMtpKJayprU-KDWhoBkY7TBGqSqIZuym2OvI6LtZ3R7G7-3px2yX7D4Uzg</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Performance Evaluation of Containerization Platforms for Control and Monitoring Devices</title><source>IEEE Xplore All Conference Series</source><creator>Manninen, Harri ; Jaaskelainen, Vesa ; Blech, Jan Olaf</creator><creatorcontrib>Manninen, Harri ; Jaaskelainen, Vesa ; Blech, Jan Olaf</creatorcontrib><description>Containerization platforms such as Docker are now common practice in the IT industry and are frequently used in combination with virtual machines in cloud-scenarios. Using containerization platforms for embedded control and monitoring devices has so far been much less common. However, the advantages such as increased modularization and portability are of relevance for embedded control devices as well. On the other hand, embedded control devices are often characterized by a limited amount of computational resources and may face other constraints such as requirements on low power consumption. This paper presents first steps on estimating the resource needs for different containerization platforms. We present empirical work on resource consumption of containerization platforms for a Raspberry Pi-based control and monitoring device and look at CPU load, memory usage and power consumption.</description><identifier>EISSN: 1946-0759</identifier><identifier>EISBN: 172818956X</identifier><identifier>EISBN: 9781728189567</identifier><identifier>DOI: 10.1109/ETFA46521.2020.9211901</identifier><language>eng</language><publisher>IEEE</publisher><subject>Containerization ; embedded monitoring and control ; Hardware ; Industries ; Memory management ; Performance evaluation ; Power demand ; Scalability ; Virtual machining</subject><ispartof>2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2020, Vol.1, p.1061-1064</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9211901$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,23910,23911,25119,27904,54533,54910</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9211901$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Manninen, Harri</creatorcontrib><creatorcontrib>Jaaskelainen, Vesa</creatorcontrib><creatorcontrib>Blech, Jan Olaf</creatorcontrib><title>Performance Evaluation of Containerization Platforms for Control and Monitoring Devices</title><title>2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)</title><addtitle>ETFA</addtitle><description>Containerization platforms such as Docker are now common practice in the IT industry and are frequently used in combination with virtual machines in cloud-scenarios. Using containerization platforms for embedded control and monitoring devices has so far been much less common. However, the advantages such as increased modularization and portability are of relevance for embedded control devices as well. On the other hand, embedded control devices are often characterized by a limited amount of computational resources and may face other constraints such as requirements on low power consumption. This paper presents first steps on estimating the resource needs for different containerization platforms. We present empirical work on resource consumption of containerization platforms for a Raspberry Pi-based control and monitoring device and look at CPU load, memory usage and power consumption.</description><subject>Containerization</subject><subject>embedded monitoring and control</subject><subject>Hardware</subject><subject>Industries</subject><subject>Memory management</subject><subject>Performance evaluation</subject><subject>Power demand</subject><subject>Scalability</subject><subject>Virtual machining</subject><issn>1946-0759</issn><isbn>172818956X</isbn><isbn>9781728189567</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2020</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotUF1LwzAUjYLgnPsFguQPtN6bNk3yOGo3hYl7mOjbSLtbiXSJpHWgv97q9nIO3PMB9zB2i5AigrmrNot5XkiBqQABqRGIBvCMXaESGrWRxds5m6DJiwSUNJds1vcfADBmC5OZCXtdU2xD3FvfEK8Otvuygwueh5aXwQ_WeYru53hbd3b48_Z8xH85ho5bv-NPwbshROff-T0dXEP9NbtobdfT7MRT9rKoNuVDsnpePpbzVeKExCEpVKbqFppcFNAKoxvVYJ1DPjIJuSMtpKJayprU-KDWhoBkY7TBGqSqIZuym2OvI6LtZ3R7G7-3px2yX7D4Uzg</recordid><startdate>20200901</startdate><enddate>20200901</enddate><creator>Manninen, Harri</creator><creator>Jaaskelainen, Vesa</creator><creator>Blech, Jan Olaf</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20200901</creationdate><title>Performance Evaluation of Containerization Platforms for Control and Monitoring Devices</title><author>Manninen, Harri ; Jaaskelainen, Vesa ; Blech, Jan Olaf</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i251t-6737bf0c4260f298c7c1b404c7ce25de8257eb55be7202889e0e5c9891b057b03</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Containerization</topic><topic>embedded monitoring and control</topic><topic>Hardware</topic><topic>Industries</topic><topic>Memory management</topic><topic>Performance evaluation</topic><topic>Power demand</topic><topic>Scalability</topic><topic>Virtual machining</topic><toplevel>online_resources</toplevel><creatorcontrib>Manninen, Harri</creatorcontrib><creatorcontrib>Jaaskelainen, Vesa</creatorcontrib><creatorcontrib>Blech, Jan Olaf</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Manninen, Harri</au><au>Jaaskelainen, Vesa</au><au>Blech, Jan Olaf</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Performance Evaluation of Containerization Platforms for Control and Monitoring Devices</atitle><btitle>2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)</btitle><stitle>ETFA</stitle><date>2020-09-01</date><risdate>2020</risdate><volume>1</volume><spage>1061</spage><epage>1064</epage><pages>1061-1064</pages><eissn>1946-0759</eissn><eisbn>172818956X</eisbn><eisbn>9781728189567</eisbn><abstract>Containerization platforms such as Docker are now common practice in the IT industry and are frequently used in combination with virtual machines in cloud-scenarios. Using containerization platforms for embedded control and monitoring devices has so far been much less common. However, the advantages such as increased modularization and portability are of relevance for embedded control devices as well. On the other hand, embedded control devices are often characterized by a limited amount of computational resources and may face other constraints such as requirements on low power consumption. This paper presents first steps on estimating the resource needs for different containerization platforms. We present empirical work on resource consumption of containerization platforms for a Raspberry Pi-based control and monitoring device and look at CPU load, memory usage and power consumption.</abstract><pub>IEEE</pub><doi>10.1109/ETFA46521.2020.9211901</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier EISSN: 1946-0759
ispartof 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2020, Vol.1, p.1061-1064
issn 1946-0759
language eng
recordid cdi_ieee_primary_9211901
source IEEE Xplore All Conference Series
subjects Containerization
embedded monitoring and control
Hardware
Industries
Memory management
Performance evaluation
Power demand
Scalability
Virtual machining
title Performance Evaluation of Containerization Platforms for Control and Monitoring Devices
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-26T23%3A53%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Performance%20Evaluation%20of%20Containerization%20Platforms%20for%20Control%20and%20Monitoring%20Devices&rft.btitle=2020%2025th%20IEEE%20International%20Conference%20on%20Emerging%20Technologies%20and%20Factory%20Automation%20(ETFA)&rft.au=Manninen,%20Harri&rft.date=2020-09-01&rft.volume=1&rft.spage=1061&rft.epage=1064&rft.pages=1061-1064&rft.eissn=1946-0759&rft_id=info:doi/10.1109/ETFA46521.2020.9211901&rft.eisbn=172818956X&rft.eisbn_list=9781728189567&rft_dat=%3Cieee_CHZPO%3E9211901%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i251t-6737bf0c4260f298c7c1b404c7ce25de8257eb55be7202889e0e5c9891b057b03%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=9211901&rfr_iscdi=true