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In recent years, there has been a significant increase in the demand for streaming of high quality videos on the smart mobile phones. In order to meet the user quality requirements, it is important to maintain the end user quality while taking the resource consumption into consideration. This demand caught the attention of the research communities and network providers to prioritize Quality of Experience (QoE) in addition to the Quality of Service (QoS). In order to meet the users’ expectations, the QoE studies have gained utmost importance, thus creating the challenge of evaluating it in such a way that the quality, cost and energy consumption are taken into account. This gave way to the concept of QoE-aware sustainable throughput, which denotes the maximal throughput at which QoE problems can be still kept at a desired level. The aim of the thesis is to determine the sustainable throughput values from the QoE perspective. The values are observed for different delay and packet loss values in wireless and mobile scenarios. The evaluation is done using the subjective video quality assessment method. In the subjective assessment method, the evaluation is done using the ITU-T recommended Absolute Category Rating (ACR). The video quality ratings are taken from the users, and are then averaged to obtain the Mean Opinion Score (MOS). The obtained scores are used for analysis in determining the sustainable throughput values from the users’ perspective. From the results it is determined that, for all the video test cases, the videos are rated better quality at low packet loss values and low delay values. The quality of the videos with the presence of delay is rated high compared to the video quality in the case of packet loss. It was observed that the high resolution videos are feeble in the presence of higher disturbances i.e. high packet loss and larger delays. From considering all the cases, it can be observed that the QoE disturbances due to the delivery issues is at an acceptable minimum for the 360px video. Hence, the 480x360 video is the threshold to sustain the video quality.

Mapping between many different applications and many different underlying technologies is very complicated. Moreover, since users need service continuity and want to get the service in a satisfactory level, firstly, their perception of the service should be measured and secondly, the changes in the underlying technologies should be transparent to users. As a result, there should be ”virtualization layer” between application layer and underlying access technologies whose job is to abstract user perception of the application in terms of network parameters and transfer these requirements to underlying layers. In this thesis, we propose a generic mathematical expression to abstract user perception of application in a unified way for different applications. Since today applications are composite applications, having a generalized expression that has the same form for various applications can ease resource management calculations. We use application service map which is based on quality of experience for resource management.

Mapping between many different applications and many different underlying technologies is very complicated. Moreover, since users need service continuity and want to get the service in a satisfactory level, firstly, their perception of the service should be measured and secondly, the changes in the underlying technologies should be transparent to users. As a result, there should be ”virtualization layer” between application layer and underlying access technologies whose job is to abstract user perception of the application in terms of network parameters and transfer these requirements to underlying layers. In this thesis, we propose a generic mathematical expression to abstract user perception of application in a unified way for different applications. Since today applications are composite applications, having a generalized expression that has the same form for various applications can ease resource management calculations. We use application service map which is based on quality of experience for resource management.

This diploma thesis focuses on the issue of evaluation VoIP services (from the perspective of QoE) and their quality in university network. It includes theoretical basics of VoIP testing, principals of QoS, and also overview of QoE/MOS measurement methods. Next part describes the test bed and methodology used for measurements and evaluating of results. Site survey results and VoIP quality measurement are evaluated at the end, followed by recommendations that can lead to better VoIP quality in MENDELU wireless network.

The demand for efficient video coding techniques has increased in the recent past, resulting in the evolution of various video compression techniques. SVC (Scalable video coding) is the recent amendment of H.264/AVC (Advanced Video Coding), which adds a new dimension by providing the possibility of encoding a video stream into a combination of different sub streams that are scalable in areas corresponding to spatial resolution, temporal resolution and quality. Introduction of the scalability aspect is an effective video coding technique in a network scenario where the client can decode the sub stream depending on the available bandwidth in the network. A graceful degradation in the video quality is expected when any of the spatial, temporal or the quality layer is removed. Still the amount of degradation in video quality has to be measured in terms of Quality of Experience (QoE) from the user’s perspective. To measure the degradation in video quality, video streams consisting of different spatial and temporal layers have been extracted and efforts have been put to remove each layer starting from a higher dependency layer or the Enhancement layer and ending up with the lowest dependency layer or the Base layer. Extraction of a temporally downsampled layer had challenges with frame interpolation and to overcome this, temporal interpolation was employed. Similarly, a spatial downsampled layer has been upsampled in the spatial domain in order to compare with the original stream. Later, an objective video quality assessment has been made by comparing the extracted substream containing fewer layers that are downsampled both spatially and temporally with the original stream containing all layers. The Mean Opinion Scores (MOS) were obtained from objective tool named Perceptual Evaluation of Video Quality (PEVQ). The experiment is carried out for each layers and also for different test videos. Subjective tests were also performed to evaluate the user experience. The results provide recommendations to SVC capable router about the video quality available for each layer and hence the network transcoder can transmit a specific layer depending on the network conditions and capabilities of the decoding device. / Efterfrågan på effektiva video kodningstekniker har ökat under de senaste åren, vilket resulterar i utvecklingen av olika tekniker videokomprimering. SVC (Scalable Video Coding) är den senaste ändringen av H.264/AVC (Advanced Video Coding), vilket ger en ny dimension genom att möjligheten att koda en videoström till en kombination av olika sub strömmar som är skalbara i områden som motsvarar rumslig upplösning, tidsupplösning och kvalitet. Introduktion av skalbarhet aspekten är en effektiv video kodningsteknik i ett nätverk scenario där kunden kan avkoda sub strömmen beroende på den tillgängliga bandbredden i nätverket. En elegant nedbrytning i videokvaliteten förväntas när någon av den rumsliga, tidsmässiga eller kvaliteten skiktet avlägsnas. Fortfarande mängden nedbrytning i videokvalitet måste mätas i termer "Quality of Experience" (QoE) från användarens perspektiv. För att mäta försämring i video-kvalitet, har videoströmmar består av olika rumsliga och tidsmässiga skikt hämtats och ansträngningar har lagts för att ta bort varje lager från ett högre beroende lager eller förbättrande lagret och slutar upp med den lägsta beroendet lagret eller basen skikt. Extraktion av ett tidsmässigt nedsamplas lager hade problem med ram interpolation och för att övervinna detta, var temporal interpolering används. På liknande sätt har en rumslig nedsamplas skikt har uppsamplas i rumsdomänen för att jämföra med den ursprungliga strömmen. Senare har en objektiv videokvalitet bedömning gjorts genom att jämföra den extraherade underströmmen med färre lager som nedsamplade både rumsligt och tidsmässigt med den ursprungliga strömmen innehållande alla lager. De genomsnittliga yttrande poäng (MOS) erhölls från objektivt verktyg som heter Perceptuell utvärdering av Videokvalitet (PEVQ). Experimentet utförs för varje skikt och även för olika test video. Subjektiva tester utfördes också för att utvärdera användarupplevelsen. Resultaten ger rekommendationer till SVC kapabel router om videokvaliteten för varje lager och därmed nätverket kodomvandlaren kan överföra ett visst lager beroende på nätverksförhållanden och kapacitet avkodnings anordningen. / Tilak Varisetty, 518, Gamlainfartsvägen, Annebo, Karlskrona -37141, Mobil: 0723060131

Mobile data traffic will continue to show rapid growth in the coming years; however the data revenue is not rising fast enough to ensure the operators’ profitability. Therefore, mobile operators must seek new approaches to find out what service does the customers need and what quality makes the customers satisfied in order to keep their increasingly sophisticated customers satisfied at the same time minimizing their revenue gap. This paper investigate the effect of mobile cellular network performance and contextual factors on smartphone users’ satisfaction, this was done via crowdsourcing through an experiment where an Android Application and a user Survey were included, which is able to evaluate and analyze the perceived quality of experience (QoE) for YouTube service for Android Smartphone users. To achieve this goal, the App NPT performs measurements of objective quality of service (QoS) parameters, whereas the survey carriers out collecting subjective user opinion. The result show that network performance parameters do impact the MOS (Mean Opinion Score) exponentially, either in a positively or negatively way, however, multiple parameters need to be considered together in order to draw a more accurate correlation with QoE. In addition, QoE are heavily affected by many other contextual factors, such as age and gender as well as users location. QoE are also impacted by several subjective factors, such as user expectation. Not always the highest throughput will lead to the best QoE, and not always the best technology (LTE) deserves the best MOS. Even though user received very high downlink throughput, their MOS value may still be low due to they might think the video were not fun to watch and the quality has not meet their expectation.

Avec l'hétérogénéité des réseaux et la demande croissante de services multimédias, la Qualité d'Expérience (QoE) devient un facteur déterminant de réussite ou d’échec de ces services. Dans cette thèse, nous avons d’abord analysé l'impact des paramètres de qualité sur l'engagement de l'utilisateur, afin de comprendre l’effet des paramètres vidéo (temps de démarrage, qualité intrinsèque, taux de blocage) et la popularité du service sur l'engagement de l'utilisateur. Nos résultats ont montré que le taux de blocage et la popularité du service sont des paramètres critiques qui impactent fortement la satisfaction et l'engagement de l’utilisateur, tandis que, le temps de démarrage a moins d’impact. Ensuite, les approches subjectives de QoE comme le Mean Opinion Score (MOS) ont été traité dans cette thèse, où les utilisateurs sont appelés à donner une note de satisfaction en fonction des informations de contextes. Une analyse statistique des résultats obtenus à partir de tests utilisateurs a montré que le type de terminal et de contenu sont des paramètres qui impactent fortement le MOS. En plus, des modèles mathématiques d’estimation de QoE en fonction des informations de contextes ont été proposés. Enfin, deux techniques d’optimisations ont été proposées : Le MDASH (MOS Dynamic Adaptive Streaming over HTTP) pour l’optimisation vidéo de flux partageant les mêmes ressources, de manière à garantir une certaine QoE pour tous les utilisateurs. Et une optimisation de livraison, basée sur des fonctions d’utilités dans laquelle, une fonction globale d'utilité est calculée en fonction de différentes contraintes (qui dépendent fortement des stratégies des acteurs de la chaîne de livraison) / With the network heterogeneity and increasing demand of multimedia services, Quality of Experience (QoE) becomes a crucial determinant of the success or failure of these services. In this thesis, we first propose to analyze the impact of quality metrics on user engagement, in order to understand the effects of video metrics (video startup time, average bitrate, buffering ratio) and content popularity on user engagement. Our results show that video buffering and content popularity are critical parameters which strongly impacts the end-user’s satisfaction and user engagement, while the video startup time appears as less significant. On other hand, we consider subjective approaches such as the Mean Opinion Score (MOS) for evaluating QoE, in which users are required to give their assessment according to contextual information. A detailed statistical analysis of our study shows the existence of non-trivial parameters impacting MOS (the type of device and the content type). We propose mathematical models to develop functional relationships between the QoE and the context information which in turn permits us to estimate the QoE. A video content optimization technique called MDASH (for MOS Dynamic Adaptive Streaming over HTTP) is proposed, which improves the perceived QoE for different video sessions sharing the same local network, while taking QoE fairness among users as a leitmotiv. We also propose a utility-based approach for video delivery optimization, in which a global utility function is computed based on different constraints (e.g. target strategies coming from the actors of the delivery chain)

The main objective of this thesis is to provide a smooth video playout on the mobile device over wireless networks. The parameters that specify the wireless channel include: bandwidth variation, frame losses, and outage time. These parameters may affect the quality of the video negatively, and the mobile users may notice sudden stops during the playout video, i.e., the picture is momentarily frozen, followed by a jump from one scene to a different one. This thesis focuses on eliminating frozen pictures and reducing the amount of video data that need to be transmitted. In order to eliminate frozen scenes on the mobile screen, we propose three different techniques. In the first technique, the video frames are split into sub-frames; these sub-frames are streamed over different channels. In the second technique the sub-frames will be “crossed” and sent together with other sub-frames that are from different positions in the streaming video sequence. If some sub-frames are lost during the transmission a reconstruction mechanism will be applied on the mobile device to recreate the missing sub-frames. In the third technique, we propose a Time Interleaving Robust Streaming (TIRS) technique to stream the video frames in different order. The benefit of that is to avoid losing a sequence of neighbouring frames. A missing frame from the streaming video will be reconstructed based on the surrounding frames on the mobile device. In order to reduce the amount of video data that are streamed over limited bandwidth channels, we propose two different techniques. These two techniques are based on identifying and extracting a high motion region of the video frames. We call this the Region Of Interest (ROI); the other parts of the video frames are called the non-Region Of Interest (non-ROI). The ROI is transmitted with high quality, whereas the non-ROI is interpolated from a number of references frames. In the first technique the ROI is a fixed size region; we considered four different types of ROI and three different scenarios. The scenarios are based on the position of the reference frames in the streaming frame sequence. In the second technique the ROI is identified based on the motion in the video frames, therefore the size, position, and shape of the ROI will be different from one video to another according to the video characteristic. The videos are coded using ffmpeg to study the effect of the proposed techniques on the encoding size. Subjective and objective metrics are used to measure the quality level of the reconstructed videos that are obtained from the proposed techniques. Mean Opinion Score (MOS) measurements are used as a subjective metric based on human opinions, while for objective metric the Structural Similarity (SSIM) index is used to compare the similarity between the original frames and the reconstructed frames.

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