RT Journal Article
T1 Measuring and estimating Key Quality Indicators in Cloud Gaming services
A1 Baena, Carlos
A1 Peñaherrera-Pulla, Oswaldo Sebastián
A1 Barco-Moreno, Raquel
A1 Fortes-Rodríguez, Sergio
K1 Videojuegos
K1 Servidores web
AB The gaming industry has proposed the concept of Cloud Gaming (CG), a paradigm that enhances the gaming experience on reduced hardware devices. However, this paradigm puts a lot of pressure on the communication links that connect the user to the cloud. As a result, the service experience becomes highly dependent on network connectivity.In this context, the present work proposes a framework for measuring and estimating the most important E2E (end-to-end) metrics of the CG service, namely Key Quality Indicators (KQIs). Therefore, different machine learning (ML) techniques are evaluated to predict KQIs related to the CG user experience. For this purpose, the most important KQIs of the service, such as input lag, freezes or perceived video frame rate, are collected in a real network deployment. The results show that ML techniques can be used to estimate these indicators solely from network-related metrics. This is seen as a valuable asset for the delivery of CG services over cellular networks, even without access to the user’s device, as it is expected for telecom operators.
PB Elsevier
YR 2023
FD 2023
LK https://hdl.handle.net/10630/26850
UL https://hdl.handle.net/10630/26850
LA eng
NO Baena, C., Peñaherrera-Pulla, O. S., Barco, R., & Fortes, S. (2022). Measuring and estimating Key Quality Indicators in Cloud Gaming services. Computer Networks (Amsterdam, Netherlands : 1999), 231, 109808–. https://doi.org/10.1016/j.comnet.2023.109808
NO inisterio de Asuntos Económicos y Transformación Digital and European Union - NextGenerationEU, Spain within the framework ‘‘Recuperación, Transformación y Resiliencia y el Mecanismo de Recuperación y Resiliencia’’ under the project MAORI. This work has been also supported by Junta de Andalucía, Spain through Secretaría General de Universidades, Investigación y Tecnología, Spain with the predoctoral grant (Ref. PREDOC_01712) as well as by Ministerio de Ciencia y Tecnología, Spain through grant FPU19/04468. Funding for open access charge: University of Málaga / CBUA
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026