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Industrial Networks and Intelligent Systems. 9th EAI International Conference, INISCOM 2023, Ho Chi Minh City, Vietnam, August 2-3, 2023, Proceedings

Research Article

MQTT-CB: Cloud Based Intelligent MQTT Protocol

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-47359-3_18,
        author={Muhammed Raşit Erol and Tuğ\`{e}e Bilen and Mehmet \O{}zdem and Berk Canberk},
        title={MQTT-CB: Cloud Based Intelligent MQTT Protocol},
        proceedings={Industrial Networks and Intelligent Systems. 9th EAI International Conference, INISCOM 2023, Ho Chi Minh City, Vietnam, August 2-3, 2023, Proceedings},
        proceedings_a={INISCOM},
        year={2023},
        month={10},
        keywords={MQTT MQTT-ST IoT LSTM Cloud Container AI},
        doi={10.1007/978-3-031-47359-3_18}
    }
    
  • Muhammed Raşit Erol
    Tuğçe Bilen
    Mehmet Özdem
    Berk Canberk
    Year: 2023
    MQTT-CB: Cloud Based Intelligent MQTT Protocol
    INISCOM
    Springer
    DOI: 10.1007/978-3-031-47359-3_18
Muhammed Raşit Erol1,*, Tuğçe Bilen2, Mehmet Özdem2, Berk Canberk1
  • 1: Department of Computer Engineering
  • 2: Innovation and Product and Service Development Directorate
*Contact email: erolm15@itu.edu.tr

Abstract

The MQTT protocol, which stands for Message Queuing Telemetry Transport, is widely recognized within the IoT community as one of the most frequently utilized communication protocols. Conventional MQTT protocols described in the literature could improve their capacity to support distributed environments and scalability. In this manner, MQTT-ST is an advanced MQTT protocol that provides bridging capabilities within a distributed environment, making it a preferred option for IoT systems. In this study, we introduce a new, intelligent, scalable, and distributed MQTT-ST-based protocol named MQTT-CB. Our approach leverages containers to improve portability, and our protocol is designed with a cloud-based architecture that streamlines deployment. The primary contribution of our research is the integration of intelligent capabilities into the MQTT-ST protocol, utilizing an LSTM (Long Short-Term Memory) network, which is the leading deep learning model. Specifically, our protocol employs predictive algorithms to foresee retransmitted packets, dynamically adjusts the number of brokers in real-time, and reduces the number of brokers when clients are inactive. Our experiments demonstrate that our protocol significantly outperforms conventional MQTT-ST protocol regarding latency between subscribers and publishers. Furthermore, our protocol adapts seamlessly to changes in the publication rate. In summary, we present a cloud-based intelligent MQTT protocol that offers significant advantages over traditional MQTT-ST protocol.

Keywords
MQTT MQTT-ST IoT LSTM Cloud Container AI
Published
2023-10-31
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-47359-3_18
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