Zenoh-based Dataflow Framework for Autonomous Vehicles

Baldoni, Gabriele; Loudet, Julien; Cominardi, Luca; Corsaro, Angelo; He, Yong

doi:10.1109/qrs-c55045.2021.00085

Cited by 6 publications

(1 citation statement)

References 10 publications

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“…Note that the generic approach taken by Zenoh-Flow makes it agnostic to the application domains. In fact, its integration into automotive and robotics applications, which mostly rely on implicit dataflow programming approaches, are two industrial verticals where Zenoh-Flow is being successfully deployed and integrated [17].…”

Section: A Data Flow Framework For the Cloud-to-things Continuummentioning

confidence: 99%

A Dataflow-Oriented Approach for Machine-Learning-Powered Internet of Things Applications

Baldoni,

Teixeira,

Guimarães

et al. 2023

Electronics

Self Cite

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The rise of the Internet of Things (IoT) has led to an exponential increase in data generated by connected devices. Machine Learning (ML) has emerged as a powerful tool to analyze these data and enable intelligent IoT applications. However, developing and managing ML applications in the decentralized Cloud-to-Things continuum is extremely complex. This paper proposes Zenoh-Flow, a dataflow programming framework that supports the implementation of End-to-End (E2E) ML pipelines in a fully decentralized manner and abstracted from communication aspects. Thus, it simplifies the development and upgrade process of the next-generation ML-powered applications in the IoT domain. The proposed framework was demonstrated using a real-world use case, and the results showcased a significant improvement in overall performance and network usage compared to the original implementation. Additionally, other of its inherent benefits are a significant step towards developing efficient and scalable ML applications in the decentralized IoT ecosystem.

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Section: A Data Flow Framework For the Cloud-to-things Continuummentioning

confidence: 99%

A Dataflow-Oriented Approach for Machine-Learning-Powered Internet of Things Applications

Baldoni,

Teixeira,

Guimarães

et al. 2023

Electronics

Self Cite

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Unleashing the power of decentralized serverless IoT dataflow architecture for the Cloud-to-Edge Continuum: a performance comparison

López Escobar,

Díaz-Redondo,

Gil-Castiñeira

2024

Ann. Telecommun.

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The advent of new computing and communication trends that link pervasive data sources and consumers, such as Edge Computing, 5G and IIoT, has led to the development of the Cloud-to-Edge Continuum in order to take advantage of the resources available in massive IoT scenarios and to conduct data analysis to leverage intelligence at all levels. This paper outlines the challenging requirements of this novel IoT context and presents an innovative IoT framework to develop dataflow applications for data-centric environments. The proposed design takes advantage of decentralized Pub/Sub communication and serverless nanoservice architecture, using novel technologies such as Zenoh and WebAssembly, respectively, to implement lightweight services along the Cloud-to-Edge infrastructure. We also describe some use cases to illustrate the benefits and concerns of the coming IoT generation, giving a communication performance comparison of Zenoh over brokered MQTT strategies. Graphical abstract

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Building Zero-touch Service Management Framework for Automotive Services Using the Smart Highway Testbed

Bello,

Kriještorac,

Pokorn

et al. 2024

2024 7th International Balkan Conference on Communications and Networking (BalkanCom)

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Zenoh-based Dataflow Framework for Autonomous Vehicles

Cited by 6 publications

References 10 publications

A Dataflow-Oriented Approach for Machine-Learning-Powered Internet of Things Applications

A Dataflow-Oriented Approach for Machine-Learning-Powered Internet of Things Applications

Unleashing the power of decentralized serverless IoT dataflow architecture for the Cloud-to-Edge Continuum: a performance comparison

Building Zero-touch Service Management Framework for Automotive Services Using the Smart Highway Testbed

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