Mobile traffic classification through physical control channel fingerprinting: A deep learning approach
HD Trinh, AF Gambin, L Giupponi… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The automatic classification of applications and services is an invaluable feature for new
generation mobile networks. Here, we propose and validate algorithms to perform this task …
generation mobile networks. Here, we propose and validate algorithms to perform this task …
Microscope: mobile service traffic decomposition for network slicing as a service
The growing diversification of mobile services imposes requirements on network
performance that are ever more stringent and heterogeneous. Network slicing aligns mobile …
performance that are ever more stringent and heterogeneous. Network slicing aligns mobile …
Estimation of static and dynamic urban populations with mobile network metadata
Communication-enabled devices routinely carried by individuals have become pervasive,
opening unprecedented opportunities for collecting digital metadata about the mobility of …
opening unprecedented opportunities for collecting digital metadata about the mobility of …
Urban anomaly detection by processing mobile traffic traces with LSTM neural networks
Detecting urban anomalies is of upmost importance for public order management, since they
can pose serious risks to public safety if not timely handled. However, monitoring large …
can pose serious risks to public safety if not timely handled. However, monitoring large …
Spotting deep neural network vulnerabilities in mobile traffic forecasting with an explainable AI lens
The ability to forecast mobile traffic patterns is key to resource management for mobile
network operators and planning for local authorities. Several Deep Neural Networks (DNN) …
network operators and planning for local authorities. Several Deep Neural Networks (DNN) …
Deep convolutional autoencoder for urban land use classification using mobile device data
Z Sun, Z Peng, Y Yu, H Jiao - International Journal of Geographical …, 2022 - Taylor & Francis
Mobile phone data can provide insightful location-based information on the interactions
between individuals and the urban environment, eg urban land-use types. Using mobile …
between individuals and the urban environment, eg urban land-use types. Using mobile …
π-ROAD: A learn-as-you-go framework for on-demand emergency slices in V2X scenarios
Vehicle-to-everything (V2X) is expected to become one of the main drivers of 5G business in
the near future. Dedicated network slices are envisioned to satisfy the stringent requirements …
the near future. Dedicated network slices are envisioned to satisfy the stringent requirements …
Identification of tidal-traffic patterns in metro-area mobile networks via matrix factorization based model
Due to the highly predictable daily movements of citizens in urban areas, mobile traffic
shows repetitive patterns with spatio-temporal variations. This phenomenon is known as …
shows repetitive patterns with spatio-temporal variations. This phenomenon is known as …
[HTML][HTML] Recognition of functional areas based on call detail records and point of interest data
With the recent emergence of big data, there has been significant progress in the study of
big data mining and rapid developments in urban computing. With the integration of …
big data mining and rapid developments in urban computing. With the integration of …
A survey of crowdsensing and privacy protection in digital city
The key pillar of developing digital city is the ubiquitous sensing of people and the
environment. Crowdsensing requires a large number of users to participate in the collection …
environment. Crowdsensing requires a large number of users to participate in the collection …