Quality of experience driven video encoding adaptation strategies for cloud gaming under network constraints

Slivar, Ivan

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doctoral thesis

Quality of experience driven video encoding adaptation strategies for cloud gaming under network constraints

Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:823938

Slivar, Ivan

University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Telecommunications

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APA 6th Edition

Slivar, I. (2021). Quality of experience driven video encoding adaptation strategies for cloud gaming under network constraints (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:823938

MLA 8th Edition

Slivar, Ivan. "Quality of experience driven video encoding adaptation strategies for cloud gaming under network constraints." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:823938

Chicago 17th Edition

Harvard

Slivar, I. (2021). 'Quality of experience driven video encoding adaptation strategies for cloud gaming under network constraints', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 03 October 2023, https://urn.nsk.hr/urn:nbn:hr:168:823938

Vancouver

Slivar I. Quality of experience driven video encoding adaptation strategies for cloud gaming under network constraints [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2023 October 03] Available at: https://urn.nsk.hr/urn:nbn:hr:168:823938

IEEE

I. Slivar, "Quality of experience driven video encoding adaptation strategies for cloud gaming under network constraints", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:823938

Cite this item: https://urn.nsk.hr/urn:nbn:hr:168:823938

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Metadata

Title	Quality of experience driven video encoding adaptation strategies for cloud gaming under network constraints
Title (croatian)	Strategije prilagodbe videokodiranja usmjerene poboljšavanju iskustvene kvalitete za igre zasnovane na računalnom oblaku uslijed ograničenja mreže
Author	Ivan Slivar
Mentor	Lea Skorin-Kapov (mentor)
Committee member	Lea Skorin-Kapov (član povjerenstva)
Granter	University of Zagreb Faculty of Electrical Engineering and Computing (Department of Telecommunications) Zagreb
Defense date and country	2021, Croatia
Scientific / art field, discipline and subdiscipline	TECHNICAL SCIENCES Computing
Universal decimal classification (UDC)	004 - Computer science and technology. Computing. Data processing
Abstract	Cloud gaming has been recognized as a promising shift in the online game industry, with the aim of implementing the ``on demand`` service concept that has achieved market success in other areas of digital entertainment such as movies and TV shows. The concepts of cloud computing are leveraged to render the game scene as a video stream which is then delivered to players in real-time. The main advantage of this approach is the capability of delivering high-quality graphics games to any type of end user device, however at the cost of high bandwidth consumption and strict latency requirements. A key challenge faced by cloud game providers lies in configuring the video encoding parameters so as to maximize player Quality of Experience (QoE) while meeting bandwidth availability constraints. The main research challenge addressed in the scope of this thesis is how to configure these parameters to meet network resource constraints while maximizing QoE, and how to categorize games for the purpose of assigning appropriate video encoding adaptation strategies. In this thesis, we present the results of six conducted empirical user studies that investigated the impact of network and video encoding parameters on user's QoE for cloud gaming. Nine different games were tested during experiments, and the collected data about overall QoE was then used as an input for QoE modeling for six of the tested games based on manipulated parameters. Furthermore, the result indicated that the same video codec configuration could be utilized for different games under low network bandwidth availability. Besides subjective studies, we gathered a large number of video gameplay traces and collected player actions from 25 different games. Based on a cluster analysis of obtained data, we propose a novel game categorization based on objective video metrics and gameplay characteristics that groups games into three game categories. The proposed categorization is then utilized for assigning appropriate video encoding adaptation strategies, proposed based on collected empirical data during subjective studies, for derived game categories. The proposed video encoding adaptation strategies are evaluated in a case study of QoE-aware resource allocation for multiple cloud gaming users sharing a bottleneck link. The results have shown that the algorithms utilizing proposed video encoding adaptation strategies achieve higher average MOS scores compared to a baseline algorithm that allocates the same amount of resources to all active players.
Abstract (croatian)	Igre zasnovane na računalnom oblaku (engl. cloud gaming) su prepoznate kao obećavajući novi trend u industriji mrežnih igara, implementirajući koncept usluge na zahtjev (engl. on demand) koji je postigao tržišni uspjeh u drugim područjima digitalne zabave, poput filmova i TV emisija. Tehnologija računarstva u oblaku je iskorištena kako bi se iscrtana scena igre u obliku video strujanja dostavila do krajnjeg korisnika u stvarnom vremenu. Glavna prednost ovog pristupa je mogućnost igranja grafički visokokvalitetnih igara na bilo kojoj vrsti uređaja, što rezultira visokim zauzećem širine propusnog pojasa mreže i strogim zahtjevima za niskim mrežnim kašnjenjem. Ključni izazov s kojim su suočeni davatelji usluga igara zasnovanih na računalnom oblaku je prilagodba parametara videokodiranja kako bi se maksimizirala korisnikova iskustvena kvaliteta (engl. Quality of Experience, QoE), poštujući ograničenja širine propusnog pojasa mreže. Glavni istraživački izazov koji je istražen u okviru ovog doktorskog rada jest kako prilagoditi ove parametre, a da se pritom maksimizira iskustvena kvaliteta i zadovolje ograničenja mrežnih resursa, te kako kategorizirati igre u svrhu dodjeljivanja odgovarajuće strategije prilagodbe videokodiranja. U ovom radu predstavljeni su rezultati šest empirijskih korisničkih studija koje su istraživale utjecaj parametara mreže i videokodiranja na korisničku iskustvenu kvalitetu za igre zasnovane na računalnom oblaku. Devet različitih igara bilo je testirano tijekom eksperimenata, te su prikupljeni podaci o sveukupnom QoE-ju korišteni za dobivanje modela za procjenu QoE-ja za šest testnih igara. Rezultati su pokazali da se ista konfiguracija video kodeka može koristiti za igre iz različitih žanrova igara tijekom ograničenja širine propusnog pojasa mreže. Pored subjektivnih studija, prikupljen je velik broj video zapisa igranja te pripadajućih igračevih akcija za 25 različitih igara. Na temelju provedene klaster analize dobivenih podataka (engl. cluster analysis), predložena je nova kategorizacija igara zasnovana na objektivnim video metrikama i karakteristikama igranja koja grupira igre u tri kategorije. Predložena kategorizacija igara je s prethodno prikupljenim empirijskim podacima korištena pri odabiru pripadajuće strategije prilagodbe videokodiranja za dobivene kategorije igara. Predložene strategije prilagodbe videokodiranja su evaluirane u studijskom slučaju dodjeljivanja resursa, koje je vođeno iskustvenom kvalitetom, korisnicima usluge igara zasnovanih na računalnom oblaku koji dijele mrežnu vezu. Rezultati su pokazali da algoritmi koji koriste predložene strategije prilagodbe videokodiranja ostvaruju veće prosječne MOS rezultate u usporedbi s osnovnim algoritmom (engl. base algorithm) koji dodjeljuje istu količinu resursa svim aktivnim igračima.
Keywords
Keywords (croatian)
Language	english
URN:NBN	urn:nbn:hr:168:823938
Study programme	Title: Computer Science Study programme type: university Study level: postgraduate Academic / professional title: Doktor znanosti (Doktor znanosti)
Catalog URL	http://lib.fer.hr/cgi-bin/koha/opac-detail.pl?biblionumber=52327
Type of resource	Text
Extent	xviii, 185 str.
File origin	Born digital
Access conditions	Open access
Terms of use
Repository	FER Repository
Created on	2022-03-09 14:13:34