Title
An experimental study of fog and cloud computing in CEP-based Real-Time IoT applications
Date Issued
01 December 2021
Access level
open access
Resource Type
journal article
Author(s)
Publisher(s)
Springer Nature
Abstract
Internet of Things (IoT) has posed new requirements to the underlying processing architecture, specially for real-time applications, such as event-detection services. Complex Event Processing (CEP) engines provide a powerful tool to implement these services. Fog computing has raised as a solution to support IoT real-time applications, in contrast to the Cloud-based approach. This work is aimed at analysing a CEP-based Fog architecture for real-time IoT applications that uses a publish-subscribe protocol. A testbed has been developed with low-cost and local resources to verify the suitability of CEP-engines to low-cost computing resources. To assess performance we have analysed the effectiveness and cost of the proposal in terms of latency and resource usage, respectively. Results show that the fog computing architecture reduces event-detection latencies up to 35%, while the available computing resources are being used more efficiently, when compared to a Cloud deployment. Performance evaluation also identifies the communication between the CEP-engine and the final users as the most time consuming component of latency. Moreover, the latency analysis concludes that the time required by CEP-engine is related to the compute resources, but is nonlinear dependent of the number of things connected.
Volume
10
Issue
1
Language
English
OCDE Knowledge area
Hardware, Arquitectura de computadoras
Subjects
Scopus EID
2-s2.0-85107544135
Source
Journal of Cloud Computing
ISSN of the container
2192113X
Sponsor(s)
This work has been partially funded by the Spanish Ministry of Science, Innovation and Universities (ref. RTI2018-098156-B-C52), by the Research Plan of the University of Castilla-La Mancha (ref. 2019-GRIN-27060), and by FONDECYT / World Bank (ref. 026-2019 FONDECYT-BM-INC.INV).
Sources of information:
Directorio de Producción Científica
Scopus