363 citations · 784 across the 20 of their papers we have counts for
3 papers · 1 filter
Atom: Neural Traffic Compression with Spatio-Temporal Graph Neural Networks
Paul Almasan, Krzysztof Rusek, Shihan Xiao +4
Storing network traffic data is key to efficient network management; however, it is becoming more challenging and costly due to the ever-increasing data transmission rates, traffic…
Enhancing 5G Radio Planning with Graph Representations and Deep Learning
Paul Almasan, José Suárez-Varela, Andra Lutu +2
The roll out of new mobile network generations poses hard challenges due to various factors such as cost-benefit tradeoffs, existing infrastructure, and new technology aspects. In…
Leveraging Spatial and Temporal Correlations for Network Traffic Compression
Paul Almasan, Krzysztof Rusek, Shihan Xiao +4
The deployment of modern network applications is increasing the network size and traffic volumes at an unprecedented pace. Storing network-related information (e.g., traffic traces…