Advancing IoT interoperability: dynamic data serialization using ThingsBoard

Main Article Content

Dmytro I. Shvaika
https://orcid.org/0009-0001-3088-3997
Andrii I. Shvaika
https://orcid.org/0009-0006-8461-3550
Volodymyr O. Artemchuk
https://orcid.org/0000-0001-8819-4564

Abstract

Benchmarking leading data serialization protocols such as schemaless JSON with binary serialization formats demonstrates the superior performance of the latter in Internet of Things (IoT) ecosystems. However, ease of integration and maintenance are equally important factors for real-world applications. IoT developers choose schemaless JSON formats for primary serialization because of their user-friendliness. However, interest in using Protocol Buffers directly at the device level in Internet of Things ecosystems is growing. Many IoT devices now transfer data exclusively via Protobuf, while others are switching to this format to improve efficiency and reduce network load. However, the static nature of Protobuf requires constant developer intervention, which undermines the scalability and versatility of the platforms, especially in cloud deployments. We explore the challenges of integrating devices that communicate exclusively through Protobuf into IoT platforms using the ThingsBoard as an example. Our study proposes a dynamic method for integrating new Protobuf-compatible devices by automating the compilation of the scheme into the platform’s code base. This approach aims to simplify integration and maintenance, which, in addition to productivity, are key factors in operating efficiency
in IoT environments.

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How to Cite
Shvaika, D.I., Shvaika, A.I. and Artemchuk, V.O., 2024. Advancing IoT interoperability: dynamic data serialization using ThingsBoard. Journal of Edge Computing [Online], 3(2), pp.126–135. Available from: https://doi.org/10.55056/jec.745 [Accessed 8 December 2024].
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Articles

How to Cite

Shvaika, D.I., Shvaika, A.I. and Artemchuk, V.O., 2024. Advancing IoT interoperability: dynamic data serialization using ThingsBoard. Journal of Edge Computing [Online], 3(2), pp.126–135. Available from: https://doi.org/10.55056/jec.745 [Accessed 8 December 2024].

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