Neural collaborative filtering for network delay matrix completion - Archive ouverte HAL Access content directly
Conference Papers Year :

Neural collaborative filtering for network delay matrix completion

(1, 2) , (1, 2) , (1, 2) , (3, 4)
1
2
3
4

Abstract

In network monitoring, delays are of great use when it comes to QoS or content distributed services. However, it is often impossible to have access to all the delay measurements within a network. This can be due to network failures or to established measurement policies. For these reasons, delay matrix completion techniques are important for an optimal network monitoring service. In this paper, we formulate the completion problem as a neural collaborative filtering problem by testing two different architectures, generalized matrix factorization and multi-layer perceptron. We evaluate these methods on two different datasets: a synthetic one generated by an autonomous system simulator, and a real-world dataset from Ripe Atlas platform. Finally, a comparative study is conducted between these neural collaborative filtering methods and standard approaches.
Fichier principal
Vignette du fichier
Neural collaborative filtering for network delay matrix completion.pdf (1013.75 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03775558 , version 1 (12-09-2022)

Licence

Attribution - CC BY 4.0

Identifiers

  • HAL Id : hal-03775558 , version 1

Cite

Sanaa GHANDI, Alexandre Reiffers-Masson, Sandrine Vaton, Thierry Chonavel. Neural collaborative filtering for network delay matrix completion. 18th International Conference on Network and Service Management, Oct 2022, Thessalonique, Greece. ⟨hal-03775558⟩
45 View
15 Download

Share

Gmail Facebook Twitter LinkedIn More