International Journal of Information and Communication Sciences
Volume 4, Issue 4, December 2019, Pages: 59-67
Received: Oct. 16, 2019;
Accepted: Nov. 13, 2019;
Published: Nov. 22, 2019
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Linh Manh Pham, Faculty of Information Technology, VNU University of Engineering and Technology, Vietnam National University, Hanoi, Vietnam
Truong-Thang Nguyen, Institute of Information Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
Manh-Dong Tran, Institute of Information Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
Cloud computing is an evolution in IT consumption and delivery which makes available self-management on the Internet with a flexible, pay-as-you-go business model. Within the context of Internet of Things, the MQTT (Message Queuing Telemetry Transport) protocol that is implemented broadly by the applications of “Publish-Subscribe” paradigm has a vital role. However, MQTT brokers are saturated easily if they have to cope with huge and speedy data generated by IoT “chatty” devices. With capability of provisioning/deprovisioning granular virtual resources, Cloud computing empowered MQTT brokers by enabling its elasticity feature. Elasticity helps the brokers deal with a very large variety of data integrated into the IoT every single day. However, there was lack of sturdy benchmarking tools that judge all the aspects of MQTT brokers in order to advocate correct elastic decision-making. This article focuses on the work of benchmarking MQTT by introducing a new developed tool called MQTTBrokerBench. With this tool, users not only can benchmark MQTT brokers but also can specify saturation points where the IoT load makes the brokers be saturated. Those saturation points can be used to set thresholds for elastic decision-making. Furthermore, the article also demonstrates the results acquired by this tool through the experiments on Windows Azure Cloud Platform.
Linh Manh Pham,
A Benchmarking Tool for Elastic MQTT Brokers in IoT Applications, International Journal of Information and Communication Sciences.
Vol. 4, No. 4,
2019, pp. 59-67.
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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