GAT-AD: Graph Attention Networks for contextual anomaly detection in network monitoring
Network anomaly detection is essential to promptly detect and fix issues in the network.
Particularly, detecting traffic anomalies enables the early detection of configuration errors …
Particularly, detecting traffic anomalies enables the early detection of configuration errors …
ChainNet: A Customized Graph Neural Network Model for Loss-Aware Edge AI Service Deployment
Edge AI seeks for the deployment of deep neural network (DNN) based services across
distributed edge devices, embedding intelligence close to data sources. Due to capacity …
distributed edge devices, embedding intelligence close to data sources. Due to capacity …
Beyond Normal: Learning Spatial Density Models of Node Mobility
Learning models of complex spatial density functions, representing the steady-state density
of mobile nodes moving on a two-dimensional terrain, can assist in network design and …
of mobile nodes moving on a two-dimensional terrain, can assist in network design and …
Practical Foreground Traffic Performance Modeling for Wide Area Network
N Gu, Y Si, C Chang, Q Wan, H Yang… - 2024 7th World …, 2024 - ieeexplore.ieee.org
The quality of service (QoS) in wide area networks (WANs) is crucial for ensuring efficient
and reliable communication. Traditional QoS evaluation approaches, such as analysis …
and reliable communication. Traditional QoS evaluation approaches, such as analysis …