An optimal container update method for edge‐cloud collaboration
Emerging computing paradigms provide field‐level service responses for users, for example, edge computing, fog computing, and MEC. Edge virtualization technologies represented by Docker can provide a platform‐independent, low‐resource‐consumption operating environment for edge service. The image‐pul...
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Veröffentlicht in: | Software, practice & experience practice & experience, 2024-04, Vol.54 (4), p.617-634 |
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creator | Zhang, Haotong Lin, Weiwei Xie, Rong Li, Shenghai Dai, Zhiyan Wang, James Z. |
description | Emerging computing paradigms provide field‐level service responses for users, for example, edge computing, fog computing, and MEC. Edge virtualization technologies represented by Docker can provide a platform‐independent, low‐resource‐consumption operating environment for edge service. The image‐pulling time of Docker is a crucial factor affecting the start‐up speed of edge services. The layer reuse mechanism of native Docker cannot fully utilize the duplicate data of node local images. In this paper, we propose a chunk reuse mechanism (CRM), which effectively targets node‐local duplicate data during container updates and reduces the volume of data transmission required for image building. We orchestrate the CRM process for cloud and remote‐cloud nodes to ensure that the resource overhead from container update data preparation and image reconstruction is within an acceptable range. The experimental results show that the CRM proposed in this paper can effectively utilize the node local duplicate data in the synchronous update of containers in multiple nodes, reduce the volume of data transmission, and significantly improve container update efficiency. |
doi_str_mv | 10.1002/spe.3232 |
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Edge virtualization technologies represented by Docker can provide a platform‐independent, low‐resource‐consumption operating environment for edge service. The image‐pulling time of Docker is a crucial factor affecting the start‐up speed of edge services. The layer reuse mechanism of native Docker cannot fully utilize the duplicate data of node local images. In this paper, we propose a chunk reuse mechanism (CRM), which effectively targets node‐local duplicate data during container updates and reduces the volume of data transmission required for image building. We orchestrate the CRM process for cloud and remote‐cloud nodes to ensure that the resource overhead from container update data preparation and image reconstruction is within an acceptable range. The experimental results show that the CRM proposed in this paper can effectively utilize the node local duplicate data in the synchronous update of containers in multiple nodes, reduce the volume of data transmission, and significantly improve container update efficiency.</description><identifier>ISSN: 0038-0644</identifier><identifier>EISSN: 1097-024X</identifier><identifier>DOI: 10.1002/spe.3232</identifier><language>eng</language><publisher>Bognor Regis: Wiley Subscription Services, Inc</publisher><subject>Cloud computing ; container ; Containers ; data duplicate ; Data transmission ; Docker ; Edge computing ; edge‐cloud collaboration ; Image reconstruction ; Nodes</subject><ispartof>Software, practice & experience, 2024-04, Vol.54 (4), p.617-634</ispartof><rights>2023 John Wiley & Sons, Ltd.</rights><rights>2024 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2932-85d9e5c12324b0341d48c74111c0123731cde8f061796eca03bbde5777f7c1c93</citedby><cites>FETCH-LOGICAL-c2932-85d9e5c12324b0341d48c74111c0123731cde8f061796eca03bbde5777f7c1c93</cites><orcidid>0000-0001-6876-1795</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fspe.3232$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fspe.3232$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Zhang, Haotong</creatorcontrib><creatorcontrib>Lin, Weiwei</creatorcontrib><creatorcontrib>Xie, Rong</creatorcontrib><creatorcontrib>Li, Shenghai</creatorcontrib><creatorcontrib>Dai, Zhiyan</creatorcontrib><creatorcontrib>Wang, James Z.</creatorcontrib><title>An optimal container update method for edge‐cloud collaboration</title><title>Software, practice & experience</title><description>Emerging computing paradigms provide field‐level service responses for users, for example, edge computing, fog computing, and MEC. 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The experimental results show that the CRM proposed in this paper can effectively utilize the node local duplicate data in the synchronous update of containers in multiple nodes, reduce the volume of data transmission, and significantly improve container update efficiency.</description><subject>Cloud computing</subject><subject>container</subject><subject>Containers</subject><subject>data duplicate</subject><subject>Data transmission</subject><subject>Docker</subject><subject>Edge computing</subject><subject>edge‐cloud collaboration</subject><subject>Image reconstruction</subject><subject>Nodes</subject><issn>0038-0644</issn><issn>1097-024X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp1kMtKw0AUhgdRsFbBRwi4cZN65pJMsiylXqCgoIK7YTJzoilpJs4kSHc-gs_okzi1bl0dOHyc__wfIecUZhSAXYUeZ5xxdkAmFEqZAhMvh2QCwIsUciGOyUkIawBKM5ZPyHzeJa4fmo1uE-O6QTcd-mTsrR4w2eDw5mxSO5-gfcXvzy_TutFGsG115bweGtedkqNatwHP_uaUPF8vnxa36er-5m4xX6WGlZylRWZLzAyNr4kKuKBWFEYKSqmBuJScGotFDTmVZY5GA68qi5mUspaGmpJPycX-bu_d-4hhUGs3-i5GqhhQMFbERpG63FPGuxA81qr3sZzfKgpqJ0hFQWonKKLpHv1oWtz-y6nHh-Uv_wMqPGaR</recordid><startdate>202404</startdate><enddate>202404</enddate><creator>Zhang, Haotong</creator><creator>Lin, Weiwei</creator><creator>Xie, Rong</creator><creator>Li, Shenghai</creator><creator>Dai, Zhiyan</creator><creator>Wang, James Z.</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-6876-1795</orcidid></search><sort><creationdate>202404</creationdate><title>An optimal container update method for edge‐cloud collaboration</title><author>Zhang, Haotong ; Lin, Weiwei ; Xie, Rong ; Li, Shenghai ; Dai, Zhiyan ; Wang, James Z.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2932-85d9e5c12324b0341d48c74111c0123731cde8f061796eca03bbde5777f7c1c93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Cloud computing</topic><topic>container</topic><topic>Containers</topic><topic>data duplicate</topic><topic>Data transmission</topic><topic>Docker</topic><topic>Edge computing</topic><topic>edge‐cloud collaboration</topic><topic>Image reconstruction</topic><topic>Nodes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Haotong</creatorcontrib><creatorcontrib>Lin, Weiwei</creatorcontrib><creatorcontrib>Xie, Rong</creatorcontrib><creatorcontrib>Li, Shenghai</creatorcontrib><creatorcontrib>Dai, Zhiyan</creatorcontrib><creatorcontrib>Wang, James Z.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Software, practice & experience</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Haotong</au><au>Lin, Weiwei</au><au>Xie, Rong</au><au>Li, Shenghai</au><au>Dai, Zhiyan</au><au>Wang, James Z.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An optimal container update method for edge‐cloud collaboration</atitle><jtitle>Software, practice & experience</jtitle><date>2024-04</date><risdate>2024</risdate><volume>54</volume><issue>4</issue><spage>617</spage><epage>634</epage><pages>617-634</pages><issn>0038-0644</issn><eissn>1097-024X</eissn><abstract>Emerging computing paradigms provide field‐level service responses for users, for example, edge computing, fog computing, and MEC. 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subjects | Cloud computing container Containers data duplicate Data transmission Docker Edge computing edge‐cloud collaboration Image reconstruction Nodes |
title | An optimal container update method for edge‐cloud collaboration |
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