In EDS ansehen

Monitoring Framework for the Performance Evaluation of an IoT Platform with Elasticsearch and Apache Kafka.

Gespeichert in:
Bibliographische Detailangaben
Titel: Monitoring Framework for the Performance Evaluation of an IoT Platform with Elasticsearch and Apache Kafka.
Autoren: Calderon, Gonzalo, del Campo, Guillermo, Saavedra, Edgar, Santamaría, Asunción
Quelle: Information Systems Frontiers; Dec2024, Vol. 26 Issue 6, p2373-2389, 17p
Schlagwörter: ARTIFICIAL intelligence, INFORMATION storage & retrieval systems, IMAGE processing, SEARCH engines, INTERNET of things
Abstract: IoT platforms are in charge of extracting and processing the data that come from IoT networks, generating additional value, and providing access to the user through usable interfaces. However, the ever growing number of devices, networks, services and applications within the IoT ecosystem, and the recently adopted edge/cloud architecture, increase the complexity. Therefore, IoT platforms should integrate monitoring and visualization tools to facilitate deployment, management and maintenance tasks. In this work, we present the implementation and performance evaluation of an IoT modular platform for distributed architectures that combines the use of Elastic Stack tools (Elasticsearch, Kibana and Beats) and Apache Kafka. We have developed a monitoring framework based on Beats agents that supervise the platform performance attending to different metrics; and adapted the Kibana visualization tools to provide friendly and accessible information to platform administrators and users. Finally, we have deployed and evaluated the IoT platform in four real use cases, identifying the factors that affect the performance of the different modules: Edge Node, Data Streaming, Cloud Server and Search Engine. [ABSTRACT FROM AUTHOR]
Copyright of Information Systems Frontiers is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Datenbank: Complementary Index
Beschreibung
Abstract:IoT platforms are in charge of extracting and processing the data that come from IoT networks, generating additional value, and providing access to the user through usable interfaces. However, the ever growing number of devices, networks, services and applications within the IoT ecosystem, and the recently adopted edge/cloud architecture, increase the complexity. Therefore, IoT platforms should integrate monitoring and visualization tools to facilitate deployment, management and maintenance tasks. In this work, we present the implementation and performance evaluation of an IoT modular platform for distributed architectures that combines the use of Elastic Stack tools (Elasticsearch, Kibana and Beats) and Apache Kafka. We have developed a monitoring framework based on Beats agents that supervise the platform performance attending to different metrics; and adapted the Kibana visualization tools to provide friendly and accessible information to platform administrators and users. Finally, we have deployed and evaluated the IoT platform in four real use cases, identifying the factors that affect the performance of the different modules: Edge Node, Data Streaming, Cloud Server and Search Engine. [ABSTRACT FROM AUTHOR]
ISSN:13873326
DOI:10.1007/s10796-023-10409-2