AppShot: A Conditional Deep Generative Model for Synthesizing Service-Level Mobile Traffic Snapshots at City Scale
- Resource Type
- Authors
- Chuanhao Sun; Kai Xu; Marco Fiore; Mahesh K. Marina; Yue Wang; Cezary Ziemlicki
- Source
- IMDEA Networks Institute Digital Repository
instname
Sun, C, Xu, K, Fiore, M, Marina, M K, Wang, Y & Ziemlicki, C 2022, ' AppShot: A Conditional Deep Generative Model for Synthesizing Service-Level Mobile Traffic Snapshots at City Scale ', IEEE Transactions on Network and Service Management, vol. 19, no. 4, pp. 4136-4150 . https://doi.org/10.1109/TNSM.2022.3199458
- Subject
- synthetic data generation
deep generative models
network slicing
Computer Networks and Communications
mobile services
Mobile network traffic data
generative adversarial networks
mobile traffic analysis
Electrical and Electronic Engineering
mobile network resource management
- Language
- English
Service-level mobile traffic data enables research studies and innovative applications with a potential to shape future service-oriented communication systems and beyond. However, real-world datasets reporting measurements at the individual service level are hard to access as such data is deemed commercially sensitive by operators. APPSHOT is a model for generating synthetic high-fidelity city-scale snapshots of service level mobile traffic. It can operate in any geographical region and relies solely on easily available spatial context information such as population density, thus allowing the generation of new and open traffic datasets for the research community. The design of APPSHOT is informed by an original characterization of service-level mobile traffic data. APPSHOT is a novel conditional GAN design instantiated by a convolutional neural network generator and two discriminators. The model features several other innovative mechanisms including multi-channel and overlapping patch based generation to address the unique challenges involved in generating mobile service traffic snapshots. Experiments with ground-truth data collected by a major European operator in multiple metropolitan areas show that APPSHOT can produce realistic network loads at the service level for areas where it has no prior traffic knowledge, and that such data can reliably support service-oriented networking studies. TRUE pub