139 citations · 369 across the 16 of their papers we have counts for
23 papers
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…
FTMRate: Collision-Immune Distance-based Data Rate Selection for IEEE 802.11 Networks
Wojciech Ciezobka, Maksymilian Wojnar, Katarzyna Kosek-Szott +2
Data rate selection algorithms for Wi-Fi devices are an important area of research because they directly impact performance. Most of the proposals are based on measuring the transm…
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…
RouteNet-Fermi: Network Modeling with Graph Neural Networks
Miquel Ferriol-Galmés, Jordi Paillisse, José Suárez-Varela +6
Network models are an essential block of modern networks. For example, they are widely used in network planning and optimization. However, as networks increase in scale and complex…
Fast Traffic Engineering by Gradient Descent with Learned Differentiable Routing
Krzysztof Rusek, Paul Almasan, José Suárez-Varela +3
Emerging applications such as the metaverse, telesurgery or cloud computing require increasingly complex operational demands on networks (e.g., ultra-reliable low latency). Likewis…
Reproducibility Companion Paper: Describing Subjective Experiment Consistency by -Value P-P Plot
Jakub Nawała, Lucjan Janowski, Bogdan Ćmiel +3
In this paper we reproduce experimental results presented in our earlier work titled "Describing Subjective Experiment Consistency by -Value P-P Plot" that was presented in the…