CGSynth: Cloud Gaming Synthesizer
Cloud gaming’s unique network traffic is challenging to reproduce for research. This demo introduces Cloud Gaming Synthe-sizer (CGSynth), a platform that generates realistic, configurable synthetic cloud gaming (CG) traffic. CGSynth captures real CGpatterns and allows their synthetic reproduction with user-defined flow/packet parameters and deterministic protocol headers. It employs a GRU for accurate, order-preserving timestamp generation and AI-based video interpolation for realistic payloads. Crucially, CGSynth integrates a QoE evaluation module using objective (e.g., SSIM) and subjective metrics (e.g., MOS) to validate synthetic traffic’s video quality and responsiveness against real streams.
Institutions
- Universidade Federal de São Carlos (BR)
- Universidade Estadual de Campinas (UNICAMP) (BR)
- Universidade Federal do Pampa (BR)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-09-08
- DOI
- https://doi.org/10.5281/zenodo.16968173
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00