Machine learning empowered computer networks

This special issue explores how emerging machine learning (ML) and artificial intelligence (AI) algorithms can help computer networks become smarter. The final goal is to disseminate cutting-edge research findings and computer network advances on innovative data-driven methodologies and technologies...

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Vydáno v:Computer networks (Amsterdam, Netherlands : 1999) Ročník 230; s. 109807
Hlavní autoři: Cerquitelli, Tania, Meo, Michela, Curado, Marilia, Skorin-Kapov, Lea, Tsiropoulou, Eirini Eleni
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.07.2023
Témata:
Computer communication networking
Cyber-physical systems
Data-driven algorithms
Explainable AI
Multimodal deep learning
Quality of service
Research findings
Resource-constrained devices
Resource-constrained devices
Multimodal deep learning
Data-driven algorithms
Explainable AI
Research findings
Computer communication networking
Quality of service
Cyber-physical systems
ISSN:1389-1286, 1872-7069
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Popis
Shrnutí:This special issue explores how emerging machine learning (ML) and artificial intelligence (AI) algorithms can help computer networks become smarter. The final goal is to disseminate cutting-edge research findings and computer network advances on innovative data-driven methodologies and technologies to grow innovation in ML-empowered communication networks. This particular issue aims to present advances on cross-cutting edge machine learning solutions tailored to the computer communication networking area, focusing on algorithmic aspects. The objective is to present which ML methodologies are the most effective and promising ones in the networking context so that they can inspire other researchers and practitioners in the research area of computer networks.
ISSN:1389-1286
1872-7069
DOI:10.1016/j.comnet.2023.109807