Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client Perspective
Today, the edge-cloud computing paradigm starts to gain increasing popularity, aiming to enable short latency, fast decision-making and intelligence at the network edge, especially for industrial applications. The container-based virtualization technology has been put on the roadmap by the industry...
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doaj-d3f3f36be37c45b6a023a727949cb3e32021-03-29T18:07:43ZengIEEEIEEE Open Journal of the Industrial Electronics Society2644-12842021-01-01215316810.1109/OJIES.2021.30559019343777Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client PerspectiveYu Liu0https://orcid.org/0000-0002-5742-1266Dapeng Lan1https://orcid.org/0000-0003-1104-5039Zhibo Pang2https://orcid.org/0000-0002-7474-4294Magnus Karlsson3https://orcid.org/0000-0002-4136-0817Shaofang Gong4Department of Science and Technology, Linköping University, Norrköping, SwedenDepartment of Informatics, University of Oslo, Oslo, NorwayABB AB, Corporate Research, Forskargränd 7, Västerås, Västmanland, SwedenDepartment of Science and Technology, Linköping University, Norrköping, SwedenDepartment of Science and Technology, Linköping University, Norrköping, SwedenToday, the edge-cloud computing paradigm starts to gain increasing popularity, aiming to enable short latency, fast decision-making and intelligence at the network edge, especially for industrial applications. The container-based virtualization technology has been put on the roadmap by the industry to implement edge-cloud computing infrastructures. Has the performance of the container-based edge-cloud computing stacks reached industry requirement? In this paper, from the industrial client perspective, we provide a performance evaluation methodology and apply it to the state-of-the-art containerization-based edge-cloud computing infrastructures. The influences of the message sending interval, payload, network bandwidth and concurrent devices on full stack latency are measured, and the processing capability of executing machine learning tasks are benchmarked. The results show that containerization on the edge does not introduce noticeable performance degradation in terms of communication, computing and intelligence capabilities, making it a promising technology for the edge-cloud computing paradigm. However, there is a large room for performance improvement between current implementation of the edge-cloud infrastructure and the demanding requirements anticipated by time-critical industrial applications. We also emphasize and showcase that partitioning of an industrial application into microservices throughout the whole stack can be considered during solution design. The proposed evaluation methodology can be a reference to users of edge-cloud computing as well as developers to get a client perspective overview of system performance.https://ieeexplore.ieee.org/document/9343777/Performance evaluationedge-cloud computingcontainerizationpartitioning |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yu Liu Dapeng Lan Zhibo Pang Magnus Karlsson Shaofang Gong |
spellingShingle |
Yu Liu Dapeng Lan Zhibo Pang Magnus Karlsson Shaofang Gong Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client Perspective IEEE Open Journal of the Industrial Electronics Society Performance evaluation edge-cloud computing containerization partitioning |
author_facet |
Yu Liu Dapeng Lan Zhibo Pang Magnus Karlsson Shaofang Gong |
author_sort |
Yu Liu |
title |
Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client Perspective |
title_short |
Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client Perspective |
title_full |
Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client Perspective |
title_fullStr |
Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client Perspective |
title_full_unstemmed |
Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client Perspective |
title_sort |
performance evaluation of containerization in edge-cloud computing stacks for industrial applications: a client perspective |
publisher |
IEEE |
series |
IEEE Open Journal of the Industrial Electronics Society |
issn |
2644-1284 |
publishDate |
2021-01-01 |
description |
Today, the edge-cloud computing paradigm starts to gain increasing popularity, aiming to enable short latency, fast decision-making and intelligence at the network edge, especially for industrial applications. The container-based virtualization technology has been put on the roadmap by the industry to implement edge-cloud computing infrastructures. Has the performance of the container-based edge-cloud computing stacks reached industry requirement? In this paper, from the industrial client perspective, we provide a performance evaluation methodology and apply it to the state-of-the-art containerization-based edge-cloud computing infrastructures. The influences of the message sending interval, payload, network bandwidth and concurrent devices on full stack latency are measured, and the processing capability of executing machine learning tasks are benchmarked. The results show that containerization on the edge does not introduce noticeable performance degradation in terms of communication, computing and intelligence capabilities, making it a promising technology for the edge-cloud computing paradigm. However, there is a large room for performance improvement between current implementation of the edge-cloud infrastructure and the demanding requirements anticipated by time-critical industrial applications. We also emphasize and showcase that partitioning of an industrial application into microservices throughout the whole stack can be considered during solution design. The proposed evaluation methodology can be a reference to users of edge-cloud computing as well as developers to get a client perspective overview of system performance. |
topic |
Performance evaluation edge-cloud computing containerization partitioning |
url |
https://ieeexplore.ieee.org/document/9343777/ |
work_keys_str_mv |
AT yuliu performanceevaluationofcontainerizationinedgecloudcomputingstacksforindustrialapplicationsaclientperspective AT dapenglan performanceevaluationofcontainerizationinedgecloudcomputingstacksforindustrialapplicationsaclientperspective AT zhibopang performanceevaluationofcontainerizationinedgecloudcomputingstacksforindustrialapplicationsaclientperspective AT magnuskarlsson performanceevaluationofcontainerizationinedgecloudcomputingstacksforindustrialapplicationsaclientperspective AT shaofanggong performanceevaluationofcontainerizationinedgecloudcomputingstacksforindustrialapplicationsaclientperspective |
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