Enabling IoT/M2M System Scalability with Fog Computing

Yuan Han Lee, Fuchun Lin*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


As increasingly more IoT/M2M devices are connected to Internet, they will cause serious congestion to IoT/M2M systems normally deployed in the cloud. Although Cloud can scale out to support more data requests, it may not be able to satisfy the low latency demanded by certain IoT/M2M applications. Fog, as an edge of Cloud, can alleviate the congested problem in the cloud and provide low latency for critical IoT/M2M applications due to its proximity to IoT/M2M devices. In this research, we propose (1) utilizing oneM2M, a global IoT/M2M standard, as the middleware to connect the cloud and the fog, (2) using Traffic Classifiers to intercept and divert IoT/M2M traffic requiring low latency to Fog and (3) deploying independent scalability mechanisms for Cloud and Fog. We demonstrate and verify our scalability design using a smart hospital use case and show that our proposed system can achieve better scalability results in terms of latency, CPU usage and power consumption compared to those with only Fog or Cloud.

Original languageEnglish
Title of host publicationIoT as a Service - 5th EAI International Conference, IoTaaS 2019, Proceedings
EditorsBo Li, Mao Yang, Zhongjiang Yan, Jie Zheng, Yong Fang
Number of pages14
ISBN (Print)9783030447502
StatePublished - Apr 2020
Event5th EAI International Conference on IoT as a Service, IoTaaS 2019 - Xi'an, China
Duration: 16 Nov 201917 Nov 2019

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume316 LNICST
ISSN (Print)1867-8211


Conference5th EAI International Conference on IoT as a Service, IoTaaS 2019


  • Cloud computing
  • Fog computing
  • IoT
  • Kubernetes
  • M2M
  • oneM2M
  • OpenStack
  • Scalability


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