A Lightweight Autoscaling Mechanism for Fog Computing in Industrial Applications

Fan Hsun Tseng, Ming Shiun Tsai, Chia Wei Tseng, Yao Tsung Yang, Chien Chang Liu, Li Der Chou

研究成果: 雜誌貢獻期刊論文同行評審

57 引文 斯高帕斯(Scopus)


Fog computing provides a more flexible service environment than cloud computing. The lightweight fog environment is suitable for industrial applications. In order to strengthen service scalability, container virtualization has been proposed and studied in recent years. It is vital to explore the tradeoff between service scalability and operating expenses. This paper integrates the hypervisor technique with container virtualization, and constructs an integrated virtualization (IV) fog platform for deploying industrial applications based on the virtual network function. This paper presents a fuzzy-based real-time autoscaling (FRAS) mechanism and implements it in the IV fog platform. The FRAS mechanism provides a dynamic, rapid, lightweight, and low-cost solution to the service autoscaling problem. Experimental results showed that the proposed FRAS mechanism yields a better service scale with lower average delay, error rate, and operating expenses compared to other autoscaling schemes.

頁(從 - 到)4529-4537
期刊IEEE Transactions on Industrial Informatics
出版狀態已出版 - 10月 2018


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