Authors:
Martin Štufi
1
and
Boris Bačić
2
Affiliations:
1
Solutia, s.r.o., Prague, Czech Republic
;
2
School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand
Keyword(s):
Sensor Networks, Big Data, Analytical Platforms, HiveMQ, MQTT, Kubernetes (K8s), Java.
Abstract:
There is a growing trend for enterprise-level Internet of Things (IoT) applications requiring real-time horizontally scalable data processing platforms. Real-time processing platforms receiving data streams from sensor networks (e.g., autonomous and connected vehicles, smart security for businesses and homes, smartwatches, fitness trackers, and other wearables) require distributed MQTT brokers. This case study presents an IoT data streaming testbed platform prepared for the Czech Post. The presented platform has met the throughput requirement of 2 million messages per 24 hours (comprising SMS and emails). The tested MQTT broker runs on a single virtual node of a horizontally scalable testbed platform. Soon the Czech Post will modernise its eServices to increase package deliveries aligned with eCommerce and eGovernment demands. The presented testbed platform fulfils all requirements, and it is also capable of processing thousands of messages per second. The presented platform and conc
epts are transferable to healthcare systems, transport operations, the automotive industry, and other domains such as smart cities.
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