DAIoTtalk: A data-decentralized pub-sub AIoT platform

Tong, Kit-Lun, Lin, Hung-Cheng, Wu, Kun-Ru, Ren, Yi, Parr, Gerard and Tseng, Yu-Chee (2025) DAIoTtalk: A data-decentralized pub-sub AIoT platform. In: in Proc. IEEE 101st Vehicular Technology Conference: VTC2025 - Spring. IEEE Vehicular Technology Conference . UNSPECIFIED, pp. 1-6. ISBN 9798331531478

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Abstract

With the advancement of Internet of Things (IoT) applications, it is essential to utilize an IoT platform to facilitate data exchange and application deployment. Existing platforms are typically either data-cloud-based or data-centralized, relying on servers as repeaters to exchange data. However, these architectures often face limitations related to triangle routing, network bottlenecks, and data scalability challenges, particularly in AIoT (Artificial Intelligence of Things) applications that require the fusion of numerous high-volume data streams. These challenges can be significantly mitigated through data-decentralized direct sender-to-receiver exchanges with a remote 'Agent', which is responsible for connectivity management. This work presents a prototype data-decentralized AIoT platform (DAIoTtalk) featuring peer-to-peer communications empowered by customized gRPC remote procedure calls based on the publish-subscribe (pub-sub) paradigm. An extension of IoTtalk, DAIoTtalk ensures device management with more adaptable node networking and offers a test bed for low-code development with decentralized communications. We demonstrate through extensive experiments that our design achieves at least 3 times more efficiency than a data-centralized approach. We also develop a case study to showcase the flexibility of our platform.

Item Type:	Book Section
Uncontrolled Keywords:	vehicular and wireless technologies,scalability,streaming media,peer-to-peer computing,virtual private networks,internet of things,servers,security,artificial intelligence,vehicle dynamics,internet of things (iot),p2p communication,artificial intelligence of things (aiot),deep learning,grpc remote procedure calls (grpc),applied mathematics,electrical and electronic engineering,computer science applications ,/dk/atira/pure/subjectarea/asjc/2600/2604
Faculty \ School:	Faculty of Science Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Data Science and AI Faculty of Science > Research Groups > Cyber Intelligence and Networks
Related URLs:	http://www.scopus.com/inward/record.url?... https://ieeexplore.ieee.org/document/111...
Depositing User:	LivePure Connector
Date Deposited:	12 Nov 2025 12:30
Last Modified:	17 Nov 2025 09:33
URI:	https://ueaeprints.uea.ac.uk/id/eprint/100959
DOI:	10.1109/VTC2025-Spring65109.2025.11174754

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