CGReplay: Capture and Replay of Cloud Gaming Traffic for QoE/QoS Assessment
Cloud Gaming (CG) research faces challenges due to the unpredictability of game engines and restricted access to commercial platforms and their logs. This creates major obstacles to conducting fair experimentation and evaluation. CGReplay captures and replays player commands and the corresponding video frames in an ordered and synchronized action-reaction loop, ensuring reproducibility. It enables Quality of Experience/Service (QoE/QoS) assessment under varying network conditions and serves as a foundation for broader CG research. The code is publicly available for further development <sup>1</sup>1https://github.com/dcomp-leris/CGReplay.git.
Authors
- Fábio L. Verdi (ORCID: https://orcid.org/0000-0002-5455-8910)
- Ariel Góes De Castro (ORCID: https://orcid.org/0000-0002-5391-5082)
- Alireza Shirmarz (ORCID: https://orcid.org/0000-0003-4296-0002)
- Christian Esteve Rothenberg (ORCID: https://orcid.org/0000-0003-3109-4305)
Institutions
- Universidade Federal de São Carlos (BR)
- Universidade Estadual de Campinas (UNICAMP) (BR)
Publication Details
- Published
- 2025-06-23
- DOI
- https://doi.org/10.1109/netsoft64993.2025.11080563
- Citations
- 1
- Primary Topic
- Image and Video Quality Assessment
- Type
- article
- Field-Weighted Citation Impact
- 1.28
Funders
- Fundação de Amparo à Pesquisa do Estado de São Paulo