| Title |
An Analysis of Computational Resources of Event-Driven Streaming Data Flow for Internet of Things: A Case Study |
| ID_Doc |
41503 |
| Authors |
Tenorio-Trigoso, A; Castillo-Cara, M; Mondragon-Ruiz, G; Carrion, C; Caminero, B |
| Title |
An Analysis of Computational Resources of Event-Driven Streaming Data Flow for Internet of Things: A Case Study |
| Year |
2023 |
| Published |
Computer Journal, 66, 1 |
| DOI |
10.1093/comjnl/bxab143 |
| Abstract |
Information and communication technologies backbone of a smart city is an Internet of Things (IoT) application that combines technologies such as low power IoT networks, device management, analytics or event stream processing. Hence, designing an efficient IoT architecture for real-time IoT applications brings technical challenges that include the integration of application network protocols and data processing. In this context, the system scalability of two architectures has been analysed: the first architecture, named as POST architecture, integrates the hyper text transfer protocol with an Extract-Transform-Load technique, and is used as baseline; the second architecture, named as MQTT-CEP, is based on a publish-subscribe protocol, i.e. message queue telemetry transport, and a complex event processor engine. In this analysis, SAVIA, a smart city citizen security application, has been deployed following both architectural approaches. Results show that the design of the network protocol and the data analytic layer impacts highly in the Quality of Service experimented by the final IoT users. The experiments show that the integrated MQTT-CEP architecture scales properly, keeps energy consumption limited and thereby, promotes the development of a distributed IoT architecture based on constraint resources. The drawback is an increase in latency, mainly caused by the loosely coupled communication pattern of MQTT, but within reasonable levels which stabilize with increasing workloads. |
| Author Keywords |
smart city; Internet of Things; real-time stream processing; computing performance; data-driven analysis; complex event processing |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000789365600001 |
| WoS Category |
Computer Science, Hardware & Architecture; Computer Science, Information Systems; Computer Science, Software Engineering; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
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