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Digital twin network: Opportunities and challenges
The proliferation of emergent network applications (eg, AR/VR, telesurgery, real-time
communications) is increasing the difficulty of managing modern communication networks …
communications) is increasing the difficulty of managing modern communication networks …
Network digital twin: Context, enabling technologies, and opportunities
The proliferation of emergent network applications (eg, telesurgery, metaverse) is increasing
the difficulty of managing modern communication networks. These applications entail …
the difficulty of managing modern communication networks. These applications entail …
An efficient design of intelligent network data plane
Deploying machine learning models directly on the network data plane enables intelligent
traffic analysis at line-speed using data-driven models rather than predefined protocols …
traffic analysis at line-speed using data-driven models rather than predefined protocols …
Reinforcement learning in practice: Opportunities and challenges
Y Li - arxiv preprint arxiv:2202.11296, 2022 - arxiv.org
This article is a gentle discussion about the field of reinforcement learning in practice, about
opportunities and challenges, touching a broad range of topics, with perspectives and …
opportunities and challenges, touching a broad range of topics, with perspectives and …
Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case
Abstract Deep Reinforcement Learning (DRL) has shown a dramatic improvement in
decision-making and automated control problems. Consequently, DRL represents a …
decision-making and automated control problems. Consequently, DRL represents a …
Unveiling the potential of graph neural networks for robust intrusion detection
The last few years have seen an increasing wave of attacks with serious economic and
privacy damages, which evinces the need for accurate Network Intrusion Detection Systems …
privacy damages, which evinces the need for accurate Network Intrusion Detection Systems …
Computers can learn from the heuristic designs and master internet congestion control
In this work, for the first time, we demonstrate that computers can automatically learn from
observing the heuristic efforts of the last four decades, stand on the shoulders of the existing …
observing the heuristic efforts of the last four decades, stand on the shoulders of the existing …
[HTML][HTML] Building a digital twin for network optimization using graph neural networks
Network modeling is a critical component of Quality of Service (QoS) optimization. Current
networks implement Service Level Agreements (SLA) by careful configuration of both routing …
networks implement Service Level Agreements (SLA) by careful configuration of both routing …
[PDF][PDF] Holographic-type communication: A new challenge for the next decade
Holographic‑Type Communication (HTC) is an important technology that will be supported
by 6G and beyond wireless systems. It provides truly immersive experiences for a large …
by 6G and beyond wireless systems. It provides truly immersive experiences for a large …
Teal: Learning-accelerated optimization of wan traffic engineering
The rapid expansion of global cloud wide-area networks (WANs) has posed a challenge for
commercial optimization engines to efficiently solve network traffic engineering (TE) …
commercial optimization engines to efficiently solve network traffic engineering (TE) …