A Measurement Study on Evaluating Container Network Performance for Edge Computing

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dc.contributor.authorYoon, Junghanko
dc.contributor.authorLi, Jianko
dc.contributor.authorShin, Sanghoko
dc.date.accessioned2021-10-28T00:50:17Z-
dc.date.available2021-10-28T00:50:17Z-
dc.date.created2021-10-19-
dc.date.issued2020-09-
dc.identifier.citation21st Asia-Pacific Network Operations and Management Symposium, APNOMS 2020, pp.345 - 348-
dc.identifier.issn2576-8565-
dc.identifier.urihttp://hdl.handle.net/10203/288394-
dc.description.abstractWith the development of cloud technology, people are focusing on lightweight container technology. Container networking is a core technology in providing high-level cloud services, and there are various implementation models such as Container Network Model (CNM) and Container Network Interface (CNI). Among them, CNI is a de-facto standard adopted by various container platforms. There are many plugins that implement the CM networking model, and the implementation method differs, showing a great difference in a view of performance. MEC (Multi-Access Edge Computing) is a technology that provides services by locating the server closest to the user who wants to use mobile communication services. In this paper, the performance was measured by applying various CM network plugins to the CoV architecture. Through this measurement, we analyzed the factors of network performance degradation. The result of the analysis is expected to be used as a good reference in constructing the CoV architecture for low latency in the future.-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleA Measurement Study on Evaluating Container Network Performance for Edge Computing-
dc.typeConference-
dc.identifier.wosid000630323900069-
dc.identifier.scopusid2-s2.0-85096986124-
dc.type.rimsCONF-
dc.citation.beginningpage345-
dc.citation.endingpage348-
dc.citation.publicationname21st Asia-Pacific Network Operations and Management Symposium, APNOMS 2020-
dc.identifier.conferencecountryKO-
dc.identifier.conferencelocationDaegu-
dc.identifier.doi10.23919/APNOMS50412.2020.9236997-
dc.contributor.nonIdAuthorLi, Jian-
dc.contributor.nonIdAuthorShin, Sangho-
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