Szczegóły publikacji
Opis bibliograficzny
RouteNet-Erlang: a Graph Neural Network for network performance evaluation / Miquel Ferriol-Galmés, Krzysztof RUSEK, José Suárez-Varela, Shihan Xiao, Xiang Shi, Xiangle Cheng, Bo Wu, Pere Barlet-Ros, Albert Cabellos-Aparicio // W: IEEE INFOCOM 2022 [Dokument elektroniczny] : IEEE Conference on Computer Communications : May 2-5, 2022, London, virtual conference. — Wersja do Windows. — Dane tekstowe. — Piscataway : IEEE, cop. 2022. — (Proceedings IEEE INFOCOM ; ISSN 2641-9874). — e-ISBN: 978-1-6654-5822-1. — S. 2018–2027. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 2027, Abstr.
Autorzy (9)
- Ferriol-Galmés Miquel
- AGHRusek Krzysztof
- Suárez-Varela José
- Xiao Shihan
- Shi Xiang
- Cheng Xiangle
- Wu Bo
- Barlet-Ros Pere
- Cabellos-Aparicio Albert
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 143823 |
|---|---|
| Data dodania do BaDAP | 2022-11-25 |
| Tekst źródłowy | URL |
| DOI | 10.1109/INFOCOM48880.2022.9796944 |
| Rok publikacji | 2022 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Institute of Electrical and Electronics Engineers (IEEE) |
| Konferencja | IEEE International Conference on Computer Communications 2022 |
| Czasopismo/seria | Proceedings (IEEE INFOCOM) |
Abstract
Network modeling is a fundamental tool in network research, design, and operation. Arguably the most popular method for modeling is Queuing Theory (QT). Its main limitation is that it imposes strong assumptions on the packet arrival process, which typically do not hold in real networks. In the field of Deep Learning, Graph Neural Networks (GNN) have emerged as a new technique to build data-driven models that can learn complex and non-linear behavior. In this paper, we present RouteNet-Erlang, a pioneering GNN architecture designed to model computer networks. RouteNet-Erlang supports complex traffic models, multi-queue scheduling policies, routing policies and can provide accurate estimates in networks not seen in the training phase. We benchmark RouteNet-Erlang against a state-of-the-art QT model, and our results show that it outperforms QT in all the network scenarios. © 2022 IEEE.
