@inproceedings{MTMT:34832880,
	title = {Empowering ISPs with Cloud Gaming User Experience Modeling: A NVIDIA GeForce NOW Use-Case},
	url = {https://m2.mtmt.hu/api/publication/34832880},
	author = {Dobreff, Gergely and Frey, Dániel and Báder, Attila and Pašić, Alija},
	booktitle = {2024 27th Conference on Innovation in Clouds, Internet and Networks (ICIN)},
	doi = {10.1109/ICIN60470.2024.10494462},
	unique-id = {34832880},
	abstract = {Cloud gaming has emerged as a cost-effective and accessible gaming solution, with platforms like NVIDIA GeForce NOW leading the way. The rapid growth of this industry, projected to reach 6.8 billion USD by 2028, has sparked the need for enhanced user experience models to optimize cloud and network infrastructure. In our study, we conducted a comprehensive analysis of the in-game performance of the popular NVIDIA GeForce NOW cloud gaming platform under varying network conditions. Our research focused on quality of service (QoS) metrics, particularly the WebRTC logs, and their relationship with user experience, defined as in-game performance. Standardized and repeatable measurements from the GeForce NOW platform were used, where the player was asked to complete training exercises of fast-paced games under different network conditions. This paper analyses and proposes machine learning (ML) models that estimate the user experience of cloud gaming. The models are trained on the low-level network- and application-related QoS metrics extracted from WebRTC logs. Our contribution demonstrates that ML models can accurately estimate in-game performance from QoS parameters, highlighting network latency's greater impact on the player's gaming experience than packet loss, bandwidth, and jitter. With our novel model, internet service providers (ISPs) can effectively estimate user experience using only network-related metrics, enabling network optimization and enhancing gaming services. This research deepens our understanding of cloud gaming user experience and offers insights for refining cloud gaming services. © 2024 IEEE.},
	keywords = {PERFORMANCE; Data Collection; Data Collection; Cost effectiveness; Quality of service; Quality of service; Cost effective; User experience; Machine learning models; Quality-of-service; Internet service providers; Quality of service metrics; Network condition; Users' experiences; Cloud gamings; Cloud gaming; user experience modeling; User experience model},
	year = {2024},
	pages = {202-209},
	orcid-numbers = {Pašić, Alija/0000-0001-6346-496X}
}

@article{MTMT:34395347,
	title = {Összefüggő hálózatok védelme nagy kiterjedésű hibák ellen},
	url = {https://m2.mtmt.hu/api/publication/34395347},
	author = {Pašić, Alija and Revisnyei, Péter and Mogyorósi, Ferenc},
	journal-iso = {ELEKTROTECHNIKA},
	journal = {ELEKTROTECHNIKA},
	volume = {116},
	unique-id = {34395347},
	issn = {0367-0708},
	year = {2023},
	pages = {25-27},
	orcid-numbers = {Pašić, Alija/0000-0001-6346-496X}
}

@inproceedings{MTMT:34238494,
	title = {Intelligent Control Plane Design for Virtual Software-Defined Networks},
	url = {https://m2.mtmt.hu/api/publication/34238494},
	author = {Babarczi, Péter and Mogyorósi, Ferenc and Pašić, Alija},
	booktitle = {2023 13th International Workshop on Resilient Networks Design and Modeling (RNDM)},
	doi = {10.1109/RNDM59149.2023.10293099},
	unique-id = {34238494},
	year = {2023},
	orcid-numbers = {Babarczi, Péter/0000-0003-1644-2172; Pašić, Alija/0000-0001-6346-496X}
}

@inproceedings{MTMT:34238479,
	title = {Disaster-Resilient Upgrade of Interdependent Networks},
	url = {https://m2.mtmt.hu/api/publication/34238479},
	author = {Pašić, Alija and Revisnyei, Péter and Mogyorósi, Ferenc},
	booktitle = {2023 13th International Workshop on Resilient Networks Design and Modeling (RNDM)},
	doi = {10.1109/RNDM59149.2023.10293104},
	unique-id = {34238479},
	year = {2023},
	orcid-numbers = {Pašić, Alija/0000-0001-6346-496X}
}

@inproceedings{MTMT:34119881,
	title = {Enhancing Machine Learning Based Solar Generation Forecasting with Time Data Utilization},
	url = {https://m2.mtmt.hu/api/publication/34119881},
	author = {Pašić, Lejla and Pašić, Azra and Pašić, Alija and Vokony, István and Bíró, József},
	booktitle = {2023 IEEE PES GTD International Conference and Exposition (GTD)},
	doi = {10.1109/GTD49768.2023.00052},
	unique-id = {34119881},
	year = {2023},
	pages = {134-138},
	orcid-numbers = {Pašić, Alija/0000-0001-6346-496X; Bíró, József/0000-0002-9729-2702}
}

@inproceedings{MTMT:34119879,
	title = {Separated Artificial Neural Network Based Distribution System State Estimation},
	url = {https://m2.mtmt.hu/api/publication/34119879},
	author = {Pašić, Lejla and Pašić, Azra and Pašić, Alija and Vokony, István and Bíró, József},
	booktitle = {2023 IEEE PES GTD International Conference and Exposition (GTD)},
	doi = {10.1109/GTD49768.2023.00087},
	unique-id = {34119879},
	year = {2023},
	pages = {320-324},
	orcid-numbers = {Pašić, Alija/0000-0001-6346-496X; Bíró, József/0000-0002-9729-2702}
}

@article{MTMT:34118597,
	title = {Mesterséges neurális hálózatok alapú kooperatív napenergia termelés-előrejelzés},
	url = {https://m2.mtmt.hu/api/publication/34118597},
	author = {Pašić, Lejla and Pašić, Azra and Pašić, Alija and Vokony, István and Bíró, József},
	journal-iso = {ELEKTROTECHNIKA},
	journal = {ELEKTROTECHNIKA},
	volume = {116},
	unique-id = {34118597},
	issn = {0367-0708},
	year = {2023},
	pages = {11-12},
	orcid-numbers = {Pašić, Alija/0000-0001-6346-496X; Bíró, József/0000-0002-9729-2702}
}

@inproceedings{MTMT:34094284,
	title = {Predicting QoE for Delay-critical services in Mobile Networks: A video conferencing case study},
	url = {https://m2.mtmt.hu/api/publication/34094284},
	author = {Dobreff, Gergely and Szalay, Márk and Molnár, Márton and Varga, L. and Ladóczki, Bence and Bader, A. and Pašić, Alija},
	booktitle = {30th International Conference on Systems, Signals and Image Processing, IWSSIP 2023},
	doi = {10.1109/IWSSIP58668.2023.10180263},
	volume = {2023-June},
	unique-id = {34094284},
	year = {2023},
	pages = {1-5},
	orcid-numbers = {Pašić, Alija/0000-0001-6346-496X}
}

@inproceedings{MTMT:34046721,
	title = {Performance of a TDOA indoor positioning solution in real-world 5G network},
	url = {https://m2.mtmt.hu/api/publication/34046721},
	author = {Revisnyei, Péter and Mogyorósi, Ferenc and Papp, Zsófia and Törős, István and Pašić, Alija},
	booktitle = {NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium},
	doi = {10.1109/NOMS56928.2023.10154362},
	unique-id = {34046721},
	year = {2023},
	pages = {1-6},
	orcid-numbers = {Pašić, Alija/0000-0001-6346-496X}
}

@inproceedings{MTMT:34017457,
	title = {Data Collection Framework for End-to-End Radio and Transport Network Quality Monitoring},
	url = {https://m2.mtmt.hu/api/publication/34017457},
	author = {Dobreff, Gergely and Szalay, Márk and Ladóczki, Bence and Molnár, Márton and Varga, László and Báder, Attila and Pašić, Alija},
	booktitle = {2023 15th International Conference on Quality of Multimedia Experience (QoMEX)},
	doi = {10.1109/QoMEX58391.2023.10178470},
	unique-id = {34017457},
	year = {2023},
	pages = {127-130},
	orcid-numbers = {Pašić, Alija/0000-0001-6346-496X}
}