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Data Consumption Pattern of MQTT Protocol for IoT Applications

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 808))

Abstract

In connecting the networks and people, the HTTP Protocol played a greater role and it is the most widely used protocol for data transfer in variety of applications. In IoT, we got to establish connections between “machines and things”. Their communication requirements were different from current needs of Internet and associated data communications. So, HTTP protocol looks quite heavy for Internet of Things (IoT) applications, due to the overheads of HTTP. Hence, we analysed the data consumption pattern of a light weight protocol Message Queue Telemetry Transport (MQTT) supported by literature study and practical validation using Orange-Pi controlled test bed. The test bed comprises PIR Motion sensor coupled with WeMos microcontroller that sends input to the Orange-Pi Gateway over MQTT Protocol. Along with the test results, this paper summarizes the benefits of using MQTT Protocol, in IoT Applications.

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Acknowledgment

We would like to thank Nokia, College of Engineering Guindy, for giving us such an opportunity to carry out this research work and for providing us the requisite resources and infrastructure for carrying out the research. Special thanks to Mr. Dinesh Birlasekaran, Mr. Wilson Anandaraj from Nokia for being a mentor and continuous inspiration towards the research on IoT.

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Correspondence to T. Reuban Gnana Asir .

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Manohar, H.L., Reuban Gnana Asir, T. (2018). Data Consumption Pattern of MQTT Protocol for IoT Applications. In: Venkataramani, G., Sankaranarayanan, K., Mukherjee, S., Arputharaj, K., Sankara Narayanan, S. (eds) Smart Secure Systems – IoT and Analytics Perspective. ICIIT 2017. Communications in Computer and Information Science, vol 808. Springer, Singapore. https://doi.org/10.1007/978-981-10-7635-0_2

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  • DOI: https://doi.org/10.1007/978-981-10-7635-0_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7634-3

  • Online ISBN: 978-981-10-7635-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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