CoNEXT-SW 2022, Proceedings of the 3rd International CoNEXT Student Workshop, December 9, 2022, Roma, Italy
This work presents a generic framework that exploits learning to improve the quality of network measurements. The main idea of this work is to reuse measures collected by the network monitoring tasks to train an ML model that learns some per-flow characteristics and improves the measurement quality re-configuring the memory according to the learned information. We applied this idea to two different monitoring tasks, we identify the main issues related to this approach and we present some preliminary results.
Type:
Conférence
City:
Roma
Date:
2022-12-09
Department:
Data Science
Eurecom Ref:
7195
Copyright:
© ACM, 2022. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CoNEXT-SW 2022, Proceedings of the 3rd International CoNEXT Student Workshop, December 9, 2022, Roma, Italy https://doi.org/10.1145/3565477.3569147
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