ProvLight: Efficient Workflow Provenance Capture on the Edge-to-Cloud Continuum-Reference-Cited by-同舟云学术

ProvLight: Efficient Workflow Provenance Capture on the Edge-to-Cloud Continuum

Published:2023-10-31 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Cluster Computing (CLUSTER)
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Author:

Rosendo Daniel¹,Mattoso Marta²,Costan Alexandru¹,Souza Renan³,Pina Débora²,Valduriez Patrick⁴,Antoniu Gabriel¹

Affiliation:

1. University of Rennes, Inria,CNRS, IRISA,Rennes,France

2. Federal University of Rio de Janeiro,Brazil

3. Oak Ridge National Laboratory,USA

4. University of Montpellier, Inria,CNRS, LIRMM,Montpellier,France

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10319881/10319941/10319957.pdf?arnumber=10319957

Reference70 articles.

1. Capturing provenance to improve the model training of pinns: first handon experiences with grid5000;silva;CILAMCE-PANACM 2021-Proceedings of the joint XLII Ibero-Latin-American Congress on Computational Methods in Engineering and III Pan-American Congress on Computational Mechanics,2021

2. Mqtt for sensor networks (mqtt-sn) protocol specification;stanford-clark;International Business Machines Corporation version 1,2013

3. Keeping track of user steering actions in dynamic workflows

4. A Comparative Evaluation of AMQP, MQTT and HTTP Protocols Using Real-Time Public Smart City Data

5. Provenance Supporting Hyperparameter Analysis in Deep Neural Networks

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