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

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

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.

Original languageEnglish
Article number8272512
Pages (from-to)4529-4537
Number of pages9
JournalIEEE Transactions on Industrial Informatics
Volume14
Issue number10
DOIs
StatePublished - Oct 2018

Keywords

  • Autoscaling
  • container virtualization
  • fog computing
  • fuzzy theory
  • virtual network function (VNF)

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