Research Article
Enabling IoT/M2M System Scalability with Fog Computing
@INPROCEEDINGS{10.1007/978-3-030-44751-9_41, author={Yuan-Han Lee and Fuchun Lin}, title={Enabling IoT/M2M System Scalability with Fog Computing}, proceedings={IoT as a Service. 5th EAI International Conference, IoTaaS 2019, Xi’an, China, November 16-17, 2019, Proceedings}, proceedings_a={IOTAAS}, year={2020}, month={6}, keywords={Scalability Cloud computing Fog computing oneM2M IoT M2M OpenStack Kubernetes}, doi={10.1007/978-3-030-44751-9_41} }- Yuan-Han Lee
Fuchun Lin
Year: 2020
Enabling IoT/M2M System Scalability with Fog Computing
IOTAAS
Springer
DOI: 10.1007/978-3-030-44751-9_41
Abstract
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.