Performance Evaluation of Containerization in Edge-Cloud Computing Stacks for Industrial Applications: A Client Perspective

• Main Authors: Yu Liu, Dapeng Lan, Zhibo Pang, Magnus Karlsson, Shaofang Gong
• Format: Article
• Language: English
• Published: IEEE 2021-01-01
• Series: IEEE Open Journal of the Industrial Electronics Society
• Subjects: Performance evaluation; edge-cloud computing; containerization; partitioning
• Online Access: https://ieeexplore.ieee.org/document/9343777/

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.