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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Software, practice & experience practice & experience, 2024-04, Vol.54 (4), p.617-634
Hauptverfasser: Zhang, Haotong, Lin, Weiwei, Xie, Rong, Li, Shenghai, Dai, Zhiyan, Wang, James Z.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 634
container_issue 4
container_start_page 617
container_title Software, practice & experience
container_volume 54
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
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2938228152</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2938228152</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2932-85d9e5c12324b0341d48c74111c0123731cde8f061796eca03bbde5777f7c1c93</originalsourceid><addsrcrecordid>eNp1kMtKw0AUhgdRsFbBRwi4cZN65pJMsiylXqCgoIK7YTJzoilpJs4kSHc-gs_okzi1bl0dOHyc__wfIecUZhSAXYUeZ5xxdkAmFEqZAhMvh2QCwIsUciGOyUkIawBKM5ZPyHzeJa4fmo1uE-O6QTcd-mTsrR4w2eDw5mxSO5-gfcXvzy_TutFGsG115bweGtedkqNatwHP_uaUPF8vnxa36er-5m4xX6WGlZylRWZLzAyNr4kKuKBWFEYKSqmBuJScGotFDTmVZY5GA68qi5mUspaGmpJPycX-bu_d-4hhUGs3-i5GqhhQMFbERpG63FPGuxA81qr3sZzfKgpqJ0hFQWonKKLpHv1oWtz-y6nHh-Uv_wMqPGaR</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2938228152</pqid></control><display><type>article</type><title>An optimal container update method for edge‐cloud collaboration</title><source>Wiley Online Library Journals Frontfile Complete</source><creator>Zhang, Haotong ; Lin, Weiwei ; Xie, Rong ; Li, Shenghai ; Dai, Zhiyan ; Wang, James Z.</creator><creatorcontrib>Zhang, Haotong ; Lin, Weiwei ; Xie, Rong ; Li, Shenghai ; Dai, Zhiyan ; Wang, James Z.</creatorcontrib><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.</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 &amp; experience, 2024-04, Vol.54 (4), p.617-634</ispartof><rights>2023 John Wiley &amp; Sons, Ltd.</rights><rights>2024 John Wiley &amp; 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 &amp; experience</title><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.</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 &amp; 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 &amp; 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 &amp; 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. 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.</abstract><cop>Bognor Regis</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/spe.3232</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0001-6876-1795</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0038-0644
ispartof Software, practice & experience, 2024-04, Vol.54 (4), p.617-634
issn 0038-0644
1097-024X
language eng
recordid cdi_proquest_journals_2938228152
source Wiley Online Library Journals Frontfile Complete
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
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-21T21%3A38%3A18IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20optimal%20container%20update%20method%20for%20edge%E2%80%90cloud%20collaboration&rft.jtitle=Software,%20practice%20&%20experience&rft.au=Zhang,%20Haotong&rft.date=2024-04&rft.volume=54&rft.issue=4&rft.spage=617&rft.epage=634&rft.pages=617-634&rft.issn=0038-0644&rft.eissn=1097-024X&rft_id=info:doi/10.1002/spe.3232&rft_dat=%3Cproquest_cross%3E2938228152%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2938228152&rft_id=info:pmid/&rfr_iscdi=true