Dissemination of edge-heavy data on heterogeneous MQTT brokers

• Published in: 2017 IEEE 6th International Conference on Cloud Networking (CloudNet) pp. 1 - 7
• Main Authors: Banno, Ryohei, Jingyu Sun, Fujita, Masahiro, Takeuchi, Susumu, Shudo, Kazuyuki
• Format: Conference Proceeding
• Language: English; Japanese
• Published: IEEE 01.09.2017
• Subjects: Benchmark testing; Computer architecture; Distributed information systems; Edge computing; Floods; Multicast algorithms; Protocols; Publish-subscribe; Quality of service; Relays; Throughput
• DOI: 10.1109/CloudNet.2017.8071523

MQTT is one of the promising protocols for exchanging IoT data. IoT data have a characteristic called "edge-heavy" which means that things at the network edge generate a massive volume of data with high locality of utilization. For dissemination of such edge-heavy data, an architecture in which multiple MQTT brokers placed at the network edges cooperate with each other is quite effective. This edge-based architecture makes latency lower, as well as reducing consumption of cloud resources. However, under this kind of architecture, heterogeneity could be a vital issue, i.e., an appropriate product of MQTT broker could vary according to the different environment of each network edge. In this paper, we propose Interworking Layer of Distributed MQTT brokers (ILDM), which enables arbitrary kinds of MQTT brokers to cooperate with each other. We provide two basic cooperation algorithms, including the way to furnish MQTT-specific functions such as QoS and Retain. To evaluate the feasibility of ILDM, we also formulate a benchmark method which can be used for both a single broker and multiple brokers. Experimental results show that the throughput of five brokers running together by ILDM is improved 4.3 times at maximum than that of single broker.