| Texto completo | |
| Autor(es): |
Shirmarz, Alireza
;
Goes de Castro, Ariel
;
Schneider Lopes, Victor Hugo
;
Verdi, Fabio
;
Luizelli, Marcelo
;
Rothenberg, Christian
Número total de Autores: 6
|
| Tipo de documento: | Artigo Científico |
| Fonte: | PROCEEDINGS OF THE 2025 ACM SIGCOMM 2025 POSTERS AND DEMOS, SIGCOMM 2025; v. N/A, p. 3-pg., 2025-01-01. |
| Resumo | |
Cloud gaming's unique network traffic is challenging to reproduce for research. This demo introduces Cloud Gaming Synthesizer (CGSynth), a platform that generates realistic, configurable synthetic cloud gaming (CG) traffic. CGSynth captures real CG patterns 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 (AU) | |
| Processo FAPESP: | 21/00199-8 - Redes e serviços inteligentes rumo 2030 (SMARTNESS) |
| Beneficiário: | Christian Rodolfo Esteve Rothenberg |
| Modalidade de apoio: | Auxílio à Pesquisa - Programa Centros de Pesquisa Aplicada |