[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 …
[HTML][HTML] Graph Neural Networks for Routing Optimization: Challenges and Opportunities
In this paper, we explore the emerging role of graph neural networks (GNNs) in optimizing
routing for next-generation communication networks. Traditional routing protocols, such as …
routing for next-generation communication networks. Traditional routing protocols, such as …
Federated spatial reuse optimization in next-generation Decentralized IEEE 802.11 WLANs
As wireless standards evolve, more complex functionalities are introduced to address the
increasing requirements in terms of throughput, latency, security, and efficiency. To unleash …
increasing requirements in terms of throughput, latency, security, and efficiency. To unleash …
FlowDT: a flow-aware digital twin for computer networks
Network modeling is an essential tool for network planning and management. It allows
network administrators to explore the performance of new protocols, mechanisms, or optimal …
network administrators to explore the performance of new protocols, mechanisms, or optimal …
Improving student learning performance in machine learning curricula: A comparative study of online problem‐solving competitions in Chinese and English‐medium …
HT Chang, CY Lin - Journal of Computer Assisted Learning, 2024 - Wiley Online Library
Background Numerous higher education institutions worldwide have adopted English‐
language‐medium computer science courses and integrated online problem‐solving …
language‐medium computer science courses and integrated online problem‐solving …
Scaling graph-based deep learning models to larger networks
Graph Neural Networks (GNN) have shown a strong potential to be integrated into
commercial products for network control and management. Early works using GNN have …
commercial products for network control and management. Early works using GNN have …
Automatic Data Generation and Optimization for Digital Twin Network
M Li, C Zhou, L Lu, Y Zhang, T Sun… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
With the rise of new applications such as AR/VR, cloud gaming, and vehicular networks,
traditional network management solutions are no longer cost-effective. Digital Twin Network …
traditional network management solutions are no longer cost-effective. Digital Twin Network …
Low complexity approaches for end-to-end latency prediction
Software Defined Networks have opened the door to statistical and AI-based techniques to
improve efficiency of networking. Especially to ensure a certain Quality of Service (QoS) for …
improve efficiency of networking. Especially to ensure a certain Quality of Service (QoS) for …
Exploring the limitations of current graph neural networks for network modeling
Graph neural networks (GNN) have recently been proposed as a technique for accurate and
cost-efficient network modeling. As an example, the GNN-based model RouteNet has shown …
cost-efficient network modeling. As an example, the GNN-based model RouteNet has shown …
Toward the development of a multi-agent cognitive networking system for the lunar environment
This paper details the development of a multi-agent cognitive system intended to optimize
networking performance in the lunar environment. One concept of the future of lunar …
networking performance in the lunar environment. One concept of the future of lunar …