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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...
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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 |
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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> |
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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 |
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