Video-on-demand streaming從90年代就在適當的科技下成為網際網路流量的龍頭，故宮教育頻道在技術上採用TCP-based video streaming，但Video streaming使得負載較一般的伺服器繁重。透過負載平衡來分散負載是可行的方式之一，但在TCP-based video streaming的技術下，還是可能遭遇服務品質之相關議題。而服務品質要求 (Quality of Service, QoS)是用來對使用者適配的服務品質表現，做具體之等級劃分的管理工具，本研究以故宮教育頻道 (iPalace Video Channel; iPalace)為標的，針對其DNS Load Balancing搭配Round Robin的運作背景，提出VM Side QoS及Client Side QoS，在VM Side設定Load rate作為指標、在Client Side則以撥放器的表現為主，設定Initial Buffering Time、Mean Rebuffering Duration以及Rebuffering Frequency共三個指標，並搭配流量的實驗操作，劃分Regular及Class情境來蒐集資料。 在分析後發現，在環境較為一致的Class情境中，Mean Rebuffering Duration與Load Rate及Rebuffering Frequency與Load Rate具有低度正相關。未來，若能在環境及客戶端的變異性有較多的控制及掌握，則可讓資料在蒐集上更為正確，讓後續的分析及探討與實際狀況更為相符。

日前行政院提出施政報告時指出，將以「挑戰二OO八」作為目標，研議一項為期六年的「國家總體建設計畫」，計畫中又以「兩兆雙星」的產業政策最受矚目，計畫中，數位內容產業是其中一環，希望能在2006年達到三千七百億台幣的產值，增加四萬個以上就業機會﹔經濟部甚至將成立「數位內容學院」，幫助數位產業培養傑出人才，強化國家的競爭力，台灣更訂定2006年為數位電視元年，全面轉換現有類比電視系統，進入數位化電視時代。 所謂「數位電視」時代，泛指數位電視之節目訊號採用數位影音訊號壓縮技術（Digital Video/Audio Compression），透過數位編碼（Digital Coding）與數位調變（Digital Modulation）來傳輸，並具有結合其他數位資料一起廣播之能力。 台灣的無線電視台早在2000 年舉行試播典禮，每天有五小時的數位節目播送﹔五大有線電視多系統經營者，（Multiple System Operator，簡稱MSO），包括東森、和信、台灣寬頻通訊顧問公司、太平洋聯網科技及其他，五大系統商掌控全台將近90%的有線電視收視戶，發展數位電視也最積極﹔衛星電視台如年代，也以衛星直播網路（Direct PC）方式播送數位電視﹔連電信業者如中華電信，更於2000年中成立「互動式多媒體處」，提供用戶互動式影音服務。 本文研究以「創新行銷」、「價值擴散」之理論為主軸，主要探討數位電視相關產業，未來能否成功，或被視聽大眾所接受，本研究之主要目的如下 一、 數位內容與創新擴散模式之關係：不同之數位電視業者，提供哪些不同　　　　　　之數位內容？能吸引哪些消費大眾 二、 數位電視之系統採用與創新擴散模式之關係 三、 數位電視之價格策略用與創新擴散模式之關係 四、 數位電視之使用簡便性與創新擴散模式之關係 本研究以歷史文獻分析法為研究主軸，蒐集國內外相關文獻、書籍、報告、期刊、論文等資料來源加以整理分析，並以國內現有之數位電視業者及其發展之商品，如何進行創新擴散，加以介紹、分析、比較，進而探討出其未來可能之發展與建議。 / The administrative Planning Report passed recently by the Executive Yuan indicates that taking [Challenge 2008] as the target, plan and discuss a 6-year plan, named [National General Construction Planning], and of which the policies for [The Two Trillion, Twin Stars] industry attracts more attention and the digital industry is one of sectors in the planning. We expect the production value would be up to NTD 370 billion in 2006, and increase more than forty thousand job opportunities; even the Ministry of Economy would establish [Digital Institute], for helping educate the outstanding talents in digital industry and sharpen the national competitive edge; and the year of 2006, which was regarded as the Digital Video Year by the Taiwan government, will witness the process of changing the simulating video system into digital video era completely. What is called [Digital Video] era, it is generally referred to the program signal for digital video adopted with Digital Video/Audio Compression technique, and through Digital Coding and Digital Modulation to transmit the message, and has the capability of broadcasting combined by other digital information. Early in 2000, the trying-out broadcasting cerebration of the Radiovision Station in Taiwan was held, and the digital program was broadcasted for five hours everyday; The big five CATV Multiple System Operator (MSO) includes Eastern Television, KG Telecom, Taiwan Broadband Communication Corporation (ANET), Pacific Broadband Company Limited, and others, which control nearly 90% CATV audiences, and develop the Digital Video actively too; The satellite TV station like ERA also broadcasts the digital video by the way of Direct PC; and the communication operator like Chunghwa Telecom established “Interactive Multimedia Office” to provide the interactive video service in 2000. The theory of “Innovative Marketing” and “Value Extending” is taken as the principle in this research, discussing mainly the digital video and interrelated industries, whether it is successful or not, or accepted by the audience. The main proposes as followings: I. The relations between digital and innovative extending; will different digital video operator provide different digital programs? What kind of audience would be attracted? II. The relations between digital video system and innovative extending model III. The relations between the price strategy of digital video and innovative extending model IV. The relations between the convenience of digital video and innovative extending model This research took historic literature analysis as its researching principle, based on the collection and analysis of interrelated literature, book, report, periodical and article etc. information in domestic and oversea, and introduce, analyze and compare how they innovate and extend upon the existing products developed by the digital video operator in domestic, and further discuss its future orientation and suggestion.

Com o aumento da concorrência sofrido pelas operadoras de telecomunicações frente à entrada de diversas empresas de outros ramos no mercado de comunicação, como, por exemplo, os Provedores de Serviço de Internet (ISPs - Internet Service Providers) através da oferta de serviços de voz sobre IP, tais operadoras viram-se obrigadas a diversificar sua oferta de serviços para gerar novas fontes de receita. Por possuírem ampla infra-estrutura instalada, as operadoras de telecomunicações passaram a oferecer, também, serviço de TV aos usuários, através de suas redes (convergentes) de telefonia e dados já existentes, o chamado IPTV. O objetivo deste trabalho foi possibilitar, neste cenário, que estas empresas consigam oferecer, além dos serviços convencionais de TV (e.g., transmissões lineares dos conteúdos nos canais de TV), serviços diferenciados empregando-se a mesma infra-estrutura. O foco deste trabalho é a oferta do serviço de apresentação deslocada no tempo dos conteúdos transmitidos linearmente nos canais de TV, sem a necessidade de configuração prévia por parte do usuário. Desta maneira, dá-se maior flexibilidade ao usuário, possibilitando-o assistir aos conteúdos que lhe interessam, no horário mais conveniente, sem ter que se preocupar com isso antecipadamente (i.e., sem a necessidade de configurar algum equipamento para gravar o conteúdo ou saber antecipadamente quais programas lhe interessam). Para isso foram pesquisadas e analisadas tanto tecnologias de transmissão e distribuição de conteúdos, como também o paradigma peer-to-peer, muito utilizado atualmente no compartilhamento de arquivos na Internet. A partir daí, foi concebida uma arquitetura capaz de oferecer tanto o serviço tradicional de transmissão linear de TV, quanto de apresentar vídeos deslocados no tempo (i.e., vídeos cuja transmissão linear já foi iniciada ou até concluída, a partir de qualquer posição já transmitida), combinando-se técnicas de multidifusão de dados, armazenamento distribuído e protocolos peer-to-peer. Desta maneira, obteve-se uma solução eficiente, utilizando-se os recursos disponíveis em todo o sistema, incluindo recursos ociosos dos usuários finais, para auxiliar no armazenamento e distribuição dos conteúdos deslocados no tempo. Finalmente, um protótipo foi desenvolvido como prova de conceito da arquitetura proposta neste trabalho, e, juntamente com os testes realizados, comprovam a viabilidade de se utilizar redes P2P para a distribuição dos conteúdos para a apresentação deslocada no tempo. / Telecommunication companies are suffering from the increasing offer of cheap and reliable voice over IP services, being forced to diversify their services looking for new revenue possibilities. Since these companies have a vast infrastructure, they are now providing TV services through the same telephony and data infrastructure, using their IP networks to offer IPTV. The goal of the present work is to allow, in this scenario, that such companies offer, additionally to the traditional TV services (e.g., the linear transmissions of the TV channels), differentiated services through the same infrastructure. The focus of the present work is, therefore, the offering of the time-shift service, allowing users to watch linear transmitted contents, time-shifted, without the need for any in-advance configuration. This approach gives more flexibility to the users, allowing them to choose the most appropriate time to watch some content without having to specify their interests in advance (i.e., without configuring some equipment to record the content or knowing in advance which programs will interest themselves). To achieve this goal, technologies for content transmission and distribution, as well as the peer-to-peer paradigm for file sharing were studied, resulting in the development of an architecture capable of offering the traditional linear transmissions service as well as the possibility of time-shift, combining multicast, distributed caching and peer-to-peer technologies. Accordingly, an efficient solution was envisioned, making use of all available resources in the system, including idle resources in the user equipments, to help in the caching and distribution of the time-shifted contents. Finally, a prototype was developed as a proof-of-concept for the designed architecture, which together with the performed tests, shows the viability of utilizing P2P networks in the distribution of time-shifted contents.

Com o aumento da concorrência sofrido pelas operadoras de telecomunicações frente à entrada de diversas empresas de outros ramos no mercado de comunicação, como, por exemplo, os Provedores de Serviço de Internet (ISPs - Internet Service Providers) através da oferta de serviços de voz sobre IP, tais operadoras viram-se obrigadas a diversificar sua oferta de serviços para gerar novas fontes de receita. Por possuírem ampla infra-estrutura instalada, as operadoras de telecomunicações passaram a oferecer, também, serviço de TV aos usuários, através de suas redes (convergentes) de telefonia e dados já existentes, o chamado IPTV. O objetivo deste trabalho foi possibilitar, neste cenário, que estas empresas consigam oferecer, além dos serviços convencionais de TV (e.g., transmissões lineares dos conteúdos nos canais de TV), serviços diferenciados empregando-se a mesma infra-estrutura. O foco deste trabalho é a oferta do serviço de apresentação deslocada no tempo dos conteúdos transmitidos linearmente nos canais de TV, sem a necessidade de configuração prévia por parte do usuário. Desta maneira, dá-se maior flexibilidade ao usuário, possibilitando-o assistir aos conteúdos que lhe interessam, no horário mais conveniente, sem ter que se preocupar com isso antecipadamente (i.e., sem a necessidade de configurar algum equipamento para gravar o conteúdo ou saber antecipadamente quais programas lhe interessam). Para isso foram pesquisadas e analisadas tanto tecnologias de transmissão e distribuição de conteúdos, como também o paradigma peer-to-peer, muito utilizado atualmente no compartilhamento de arquivos na Internet. A partir daí, foi concebida uma arquitetura capaz de oferecer tanto o serviço tradicional de transmissão linear de TV, quanto de apresentar vídeos deslocados no tempo (i.e., vídeos cuja transmissão linear já foi iniciada ou até concluída, a partir de qualquer posição já transmitida), combinando-se técnicas de multidifusão de dados, armazenamento distribuído e protocolos peer-to-peer. Desta maneira, obteve-se uma solução eficiente, utilizando-se os recursos disponíveis em todo o sistema, incluindo recursos ociosos dos usuários finais, para auxiliar no armazenamento e distribuição dos conteúdos deslocados no tempo. Finalmente, um protótipo foi desenvolvido como prova de conceito da arquitetura proposta neste trabalho, e, juntamente com os testes realizados, comprovam a viabilidade de se utilizar redes P2P para a distribuição dos conteúdos para a apresentação deslocada no tempo. / Telecommunication companies are suffering from the increasing offer of cheap and reliable voice over IP services, being forced to diversify their services looking for new revenue possibilities. Since these companies have a vast infrastructure, they are now providing TV services through the same telephony and data infrastructure, using their IP networks to offer IPTV. The goal of the present work is to allow, in this scenario, that such companies offer, additionally to the traditional TV services (e.g., the linear transmissions of the TV channels), differentiated services through the same infrastructure. The focus of the present work is, therefore, the offering of the time-shift service, allowing users to watch linear transmitted contents, time-shifted, without the need for any in-advance configuration. This approach gives more flexibility to the users, allowing them to choose the most appropriate time to watch some content without having to specify their interests in advance (i.e., without configuring some equipment to record the content or knowing in advance which programs will interest themselves). To achieve this goal, technologies for content transmission and distribution, as well as the peer-to-peer paradigm for file sharing were studied, resulting in the development of an architecture capable of offering the traditional linear transmissions service as well as the possibility of time-shift, combining multicast, distributed caching and peer-to-peer technologies. Accordingly, an efficient solution was envisioned, making use of all available resources in the system, including idle resources in the user equipments, to help in the caching and distribution of the time-shifted contents. Finally, a prototype was developed as a proof-of-concept for the designed architecture, which together with the performed tests, shows the viability of utilizing P2P networks in the distribution of time-shifted contents.

De nos jours, l’expérience de l'utilisateur appelé en anglais « User Experience » est devenue l’un des indicateurs les plus pertinents pour les fournisseurs de services ainsi que pour les opérateurs de télécommunication pour analyser le fonctionnement de bout en bout de leurs systèmes (du terminal client, en passant par le réseaux jusqu’à l’infrastructure des services etc.). De plus, afin d’entretenir leur part de marché et rester compétitif, les différents opérateurs de télécommunication et les fournisseurs de services doivent constamment conserver et accroître le nombre de souscription des clients. Pour répondre à ces exigences, ils doivent disposer de solutions efficaces de monitoring et d’estimation de la qualité d'expérience (QoE) afin d’évaluer la satisfaction de leur clients. Cependant, la QoE est une mesure qui reste subjective et son évaluation est coûteuse et fastidieuse car elle nécessite une forte participation humaine (appelé panel de d’évaluation). Par conséquent, la conception d’un outil qui peut mesurer objectivement cette qualité d'expérience avec une précision raisonnable et en temps réel est devenue un besoin primordial qui constitue un challenge intéressant à résoudre. Comme une première contribution, nous avons analysé l'impact du comportement d’un réseau sur la qualité des services de vidéo à la demande (VOD). Nous avons également proposé un outil d'estimation objective de la QoE qui utilise le système expert basé sur la logique floue pour évaluer la QoE à partir des paramètres de qualité de service de la couche réseau. Dans une deuxième contribution, nous avons analysé l'impact des paramètres QoS de couche MAC sur les services de VoD dans le cadre des réseaux sans fil IEEE 802.11n. Nous avons également proposé un outil d'estimation objective de la QoE qui utilise le réseau aléatoire de neurones pour estimer la QoE dans la perspective de la couche MAC. Pour notre troisième contribution, nous avons analysé l'effet de différents scénarios d'adaptation sur la QoE dans le cadre du streaming adaptatif au débit. Nous avons également développé une plate-Forme Web de test subjectif qui peut être facilement intégré dans une plate-Forme de crowd-Sourcing pour effectuer des tests subjectifs. Finalement, pour notre quatrième contribution, nous avons analysé l'impact des différents paramètres de qualité de service Web sur leur QoE. Nous avons également proposé un algorithme d'apprentissage automatique i.e. un système expert hybride rugueux basé sur la logique floue pour estimer objectivement la QoE des Web services / Today user experience is becoming a reliable indicator for service providers and telecommunication operators to convey overall end to end system functioning. Moreover, to compete for a prominent market share, different network operators and service providers should retain and increase the customers’ subscription. To fulfil these requirements they require an efficient Quality of Experience (QoE) monitoring and estimation. However, QoE is a subjective metric and its evaluation is expensive and time consuming since it requires human participation. Therefore, there is a need for an objective tool that can measure the QoE objectively with reasonable accuracy in real-Time. As a first contribution, we analyzed the impact of network conditions on Video on Demand (VoD) services. We also proposed an objective QoE estimation tool that uses fuzzy expert system to estimate QoE from network layer QoS parameters. As a second contribution, we analyzed the impact of MAC layer QoS parameters on VoD services over IEEE 802.11n wireless networks. We also proposed an objective QoE estimation tool that uses random neural network to estimate QoE from the MAC layer perspective. As our third contribution, we analyzed the effect of different adaption scenarios on QoE of adaptive bit rate streaming. We also developed a web based subjective test platform that can be easily integrated in a crowdsourcing platform for performing subjective tests. As our fourth contribution, we analyzed the impact of different web QoS parameters on web service QoE. We also proposed a novel machine learning algorithm i.e. fuzzy rough hybrid expert system for estimating web service QoE objectively

Il y a de nouveaux défis dans l'administration et dans la conception des systèmes pour optimiser la gestion des ressources des applications basées en nuage Cloud Computing. Certaines applications demandent des performances rigoureuses (par exemple, par rapport aux retards et aux limites de la gigue), tandis que d'autres applications présentent des charges de travail en rafale (volatiles). Cette thèse propose un framework inspiré dans un modèle épidémique (et basé sur des Chaînes de Markov à Temps Continu), qui peut reproduire la volatilité de la charge de travail, à savoir les effets de buzz (quand il y a une augmentation soudaine de la popularité d'un contenu) d'un système de Vidéo à la Demande (VoD). Deux méthodes d'estimation (basés sur des heuristiques et des Chaînes de Markov Monte Carlo - MCMC) ont été également proposées dans ce travail, de façon à ajuster le modèle selon les comportements de la charge de travail. Les paramètres du modèle obtenus à partir des procédures d'étalonnage révèlent des propriétés intéressantes du modèle. Basé sur des simulations numériques, la précision des deux procédures a été analysée, en montrant que les deux présentent des performances raisonnables. Toutefois, la méthode MCMC dépasse la performance de l'approche heuristique. Cette thèse compare également le modèle proposé avec d'autres modèles existants, tout en examinant la qualité de l'ajustement de certaines propriétés statistiques sur des traces réelles de la charge de travail. Finalement, ce travail propose une approche probabiliste de provisionnement des ressources, basée sur le Principe de Grandes Déviations (LDP). LDP caractérise statistiquement les effets de buzz, qui causent de la volatilité extrême de la charge de travail. Cette analyse exploite les informations obtenues en utilisant le LPD du système VoD pour la définition des politiques de gestion des ressources. Ces politiques peuvent être intéressantes pour toutes les acteurs dans le nouveau contexte de l'informatique en nuage. / There are some new challenges in system administration and design to optimize the resource management for a cloud based application. Some applications demand stringent performance requirements (e.g. delay and jitter bounds), while some applications exhibit bursty (volatile) workloads. This thesis proposes an epidemic model inspired (and continuous time Markov Chain based) framework, which can reproduce workload volatility namely the "buzz effects" (when there is a sudden increase of a content popularity) of a Video on Demand (VoD) system. Two estimation procedures (heuristic and a Markov Chain Monte Carlo (MCMC) based approach) have also been proposed in this work to calibrate the model against workload traces. Obtained model parameters from the calibration procedures reveal some interesting property of the model. Based on numerical simulations, precisions of both procedures have been analyzed, which show that both of them perform reasonably. However, the MCMC procedure outperforms the heuristic approach. This thesis also compares the proposed model with other existing models examining the goodness-of-fit of some statistical properties of real workload traces. Finally this work suggests a probabilistic resource provisioning approach based on a Large Deviation Principle (LDP). LDP statistically characterizes the buzz effects that causeextreme workload volatility. This analysis exploits the information obtained using the LDP of the VoD system for defining resource management policies. These policies may be of some interest to all stakeholders in the emerging context of cloud networking.

Sedan 2013 har allt fler börjat använda sig av streamingtjänster för film och TV på internet (Findahl,2014). I takt med att användningen ökar är det viktigt att tjänsterna är välutvecklade och lättillgängliga för användaren. I denna uppsats undersöker vi funktioner på de tre största Video on Demand-tjänsterna (VoD) i Sverige ur ett användarperspektiv. Med hjälp av befintliga teorier och litteratur diskuterar vi användarbarhet och genomför en områdesanalys av de utvalda VoD-tjänsterna. Utifrån analysen har vi gått vidare med tio funktioner för att avgränsa studien. Uppsatsen innehåller två metoder; fokus grupper och enkätundersökning. Resultatet från dessa metoder presenteras i en rankningslista som ska fungera som rekommendation till operatörerna. Slutsatsen som kan dras från resultatet är att en VoD-tjänst som har flera eller alla av funktioner från rankningslistan tillgängliga, kommer ge användare en betydligt bättre användarupplevelse på webbplatsen. / The development of streaming media services has rapidly evolved since 2013 (Findahl, 2014). As the usage of video on demand (VOD) services increases, it becomes more important that the services are well developed and accessible to its users. In this essay we study the functionality of the three most used VOD-services in Sweden, from a user perspective. Using existing theories and literature, we discussusability and conduct a field evaluation, analysing the three VOD services. Based on the conducted evaluation, we decided to move forward with ten features that, we found, were the most useful from a user perspective. It also helped delimit the study. The essay contains two research methods, a questionnaire survey and focus groups. The results from the study are presented in a ranking-list that will serve as a recommendation to the operators of the VOD services. The conclusion we made from the ranking-list is that a VOD service that take most of these functions into account will make for a better user experience.

La généralisation de l’usage de l’Internet, ces dernières années, a été marquée par deux tendances importantes. Nous citerons en premier, l’enthousiasme de plus en plus grand des utilisateurs pour les services médias. Cette tendance est particulièrement accentuée par l’avènement des contenus générés par les utilisateurs qui amènent dans les catalogues des fournisseurs de services un choix illimité de contenus. L’autre tendance est la diversification et l’hétérogénéité en ressources des terminaux et réseaux d’accès. Seule la valeur du service lui-même compte aujourd’hui pour les utilisateurs et non le moyen d’y accéder. Cependant, offrir aux utilisateurs un accès ubiquitaire à de plus en plus de services Internet, impose des exigences très rigoureuses sur l’infrastructure actuelle de l’Internet. En effet, L’évolution de l’Internet devient aujourd’hui une évidence et cette évolution est d’autant plus nécessaire dans un contexte de services multimédias qui sont connus pour leur sensibilité au contexte dans lequel ils sont consommés et pour générer d’énormes quantités de trafic. Dans le cadre de cette thèse, nous nous focalisons sur deux enjeux importants dans l’évolution de l’Internet. A savoir, faciliter le déploiement de services médias personnalisés et adaptatifs et améliorer les plateformes de distribution de ces derniers afin de permettre leur passage à l’échelle tout en gardant la qualité de service à un niveau satisfaisant pour les utilisateurs finaux. Afin de permettre ceci, nous introduisons en premier, une nouvelle architecture multi environnements et multi couches permettant un environnement collaboratif pour le partage et la consommation des services médias dans un cadre des réseaux média du futur. Puis, nous proposons deux contributions majeures que nous déployons sur la couche virtuelle formés par les Home-Boxes (passerelles résidentielles évoluées) introduite dans l’architecture précédente. Dans notre première contribution, nous proposons un environnement permettant le déploiement à grande échelle de services sensibles au contexte. Deux approches ont été considérées dans la modélisation et la gestion du contexte. La première approche est basée sur les langages de balisage afin de permettre un traitement du contexte plus léger et par conséquent des temps de réponse très petits. La seconde approche, quant à elle est basée sur les ontologies et les règles afin de permettre plus d’expressivité et un meilleur partage et réutilisation des informations de contexte. Les ontologies étant connues pour leur complexité, le but de cette proposition et de prouver la faisabilité d’une telle approche dans un contexte de services multimédias par des moyen de distribution de la gestion du contexte. Concernant notre deuxième contribution, l’idée et de tirer profit des ressources (disque et connectivité) des Home-Boxes déjà déployées, afin d’améliorer les plateformes de distribution des services médias et d’améliorer ainsi le passage à l’échelle, la performance et la fiabilité de ces derniers et ce, à moindre coût. Pour cela, nous proposons deux solutions pour deux problèmes communément traités dans la réplication des contenus : (1) la redirection de requêtes pour laquelle nous proposons un algorithme de sélection à deux niveaux de filtrage, un premier filtrage basé sur les règles afin de personnaliser les services en fonction du contexte de leur consommation suivi d’un filtrage basé sur des métriques réseaux (charges des serveurs et délais entre les serveurs et les clients) ; et (2) le placement et la distribution des contenus sur les caches pour lesquels on a proposé une stratégie de mise en cache online, basée sur la popularité des contenus. / Users’ willingness to consume media services along with the compelling proliferation of mobile devices interconnected via multiple wired and wireless networking technologies place high requirements on the Future Internet. It is a common belief today that Internet should evolve towards providing end users with ubiquitous and high quality media services and this, in a scalable, reliable, efficient and interoperable way. However, enabling such a seamless media delivery raises a number of challenges. On one hand, services should be more context-aware to enable their delivery to a large and disparate computational context. On another hand, current Internet media delivery infrastructures need to scale in order to meet the continuously growing number of users while keeping quality at a satisfying level. In this context, we introduce a novel architecture, enabling a novel collaborative framework for sharing and consuming Media Services within Future Internet (FI). The introduced architecture comprises a number of environments and layers aiming to improve today’s media delivery networks and systems towards a better user experience. In this thesis, we are particulary interested in enabling context-aware multimedia services provisioning that meets on one hand, the users expectations and needs and on another hand, the exponentially growing users’ demand experienced by these services. Two major and demanding challenges are then faced in this thesis (1) the design of a context-awareness framework that allows adaptive multimedia services provisioning and, (2) the enhancement of the media delivery platform to support large-scale media services. The proposed solutions are built on the newly introduced virtual Home-Box layer in the latter proposed architecture.First, in order to achieve context-awareness, two types of frameworks are proposed based on the two main models for context representation. The markup schemes-based framework aims to achieve light weight context management to ensure performance in term of responsiveness. The second framework uses ontology and rules to model and manage context. The aim is to allow higher formality and better expressiveness and sharing. However, ontology is known to be complex and thus difficult to scale. The aim of our work is then to prove the feasibility of such a solution in the field of multimedia services provisioning when the context management is distributed among the Home-Box layer. Concerning the media services delivery enhancement, the idea is to leverage the participating and already deployed Home-Boxes disk storage and uploading capabilities to achieve service performance, scalability and reliability. Towards this, we have addressed two issues that are commonly induced by the content replication: (1) the server selection for which we have proposed a two-level anycast-based request redirection strategy that consists in a preliminary filtering based on the clients’ contexts and in a second stage provides accurate network distance information, using not only the end-to-end delay metric but also the servers’ load one and, (2) the content placement and replacement in cache for which we have designed an adaptive online popularity-based video caching strategy among the introduced HB overlay.

This thesis contains a usability evaluation of “Barnplay”, a Swedish video-on-demand service targeted at children. The objective of the study was to identify usability issues in the video service and to develop measures on improving the user interface, with special focus on adaptation to the broad target group of 3-11 year olds. The study was conducted by first mapping established practices in designs of VOD-services targeted at children, followed by interviews and usability tests with children between 2-11 concerning their use of “Barnplay”. Based on the initial data collection, a prototype was developed and then evaluated by usability testing and A/B-testing. The main conclusion of the study is the need of better individual adjustment of the video content selection to better appeal to different age segments within the target group. A design proposal, for a list of personal viewing history, was produced for displaying what the user recently had watched. / Detta examensarbete är en användbarhetsutvärdering av SVTs barnanpassade videotjänst, Barnplay. Arbetets mål är att identifiera användbarhetsproblem i videotjänsten och att ta fram åtgärder för att förbättra användargränssnittet, med särskilt fokus på anpassning till den breda målgruppen 3-11 år. Studien utfördes genom kartläggning av praxis vid design av VOD-tjänster riktade till barn, intervjuer och tester med barn mellan 2-11år kring deras användande av Barnplay. Utifrån den inledande datainsamlingen utarbetades en prototyp som utvärderades med användningstest samt A/B-test. Den viktigaste slutsatsen i studien var behovet av individuell anpassning av utbudet i videotjänsten för att bättre tilltala de olika ålderssegmenten inom målgruppen. Designförslaget som togs fram var en personlig historik-lista som visar de senast “tittade” titlarna.

For over 4 years now, there has been a fierce fight for staying ahead in the so-called ”Streaming War”. The Covid-19 pandemic and its consequent confinement only worsened the situation. In such a market where the user is faced with too many streaming video services to choose from, retaining customers becomes a necessary must. Moreover, an extensive catalogue makes it even more difficult for the user to choose a movie from. Recommender Systems try to ease this task by analyzing the users’ interactions with the platform and predicting movies that, a priori, will be watched next. Neural Networks have started to be implemented as the underlying technology in the development of Recommender Systems. Yet, most streaming services fall victim to a highly uneven movies distribution, where a small fraction of their content is watched by most of their users, having the rest of their catalogue a limited number of views. This is the long-tail problem that makes for a difficult classification model. An RNN model was implemented to solve this problem. Following a multiple-experts classification strategy, where each classifier focuses only on a specific group of films, movies are clustered by popularity. These clusters were created following the Jenks natural breaks algorithm, clustering movies by minimizing the inner group variance and maximizing the outer group variance. This new implementation ended up outperforming other clustering methods, where the proposed Jenks’ movie clusters gave better results for the corresponding models. The model had, as input, an ordered stream of watched movies. An extra input variable, the date of the visualization, gave an increase in performance, being more noticeable in those clusters with a fewer amount of movies and more views, i.e., those clusters not corresponding to the least popular ones. The addition of an extra variable, the percent of movies watched, gave inconclusive results due to hardware limitations. / I över fyra år har det nu varit en hård kamp för att ligga i framkant i det så kallade ”Streaming kriget”. Covid-19-pandemin och den därpå följande karantänen förvärrade bara situationen. På en sådan marknad där användaren står inför alltför många streamingtjänster att välja mellan, blir kvarhållande av kunderna en nödvändighet. En omfattande katalog gör det dessutom ännu svårare för användaren att välja en film. Rekommendationssystem försöker underlätta denna uppgift genom att analysera användarnas interaktion med plattformen och förutsäga vilka filmer som kommer att ses härnäst. Neurala nätverk har börjat användas som underliggande teknik vid utvecklingen av rekommendationssystem. De flesta streamingtjänster har dock en mycket ojämn fördelning av filmerna, då en liten del av deras innehåll ses av de flesta av användarna, medan en stor del av deras katalog har ett begränsat antal visualiseringar. Detta så kallade ”Long Tail”-problem gör det svårt att skapa en klassificeringsmodell. En RNN-modell implementerades för att lösa detta problem. Genom att följa en klassificeringsstrategi med flera experter, där varje klassificerare endast fokuserar på en viss grupp av filmer, grupperas filmerna efter popularitet. Dessa kluster skapades enligt Jenks natural breaks-algoritm, som klustrar filmer genom att minimera variansen i den inre gruppen och maximera variansen i den yttre gruppen. Denna nya implementering överträffade till slut andra klustermetoder, där filmklustren föreslagna av Jenks gav bättre resultat för motsvarande modeller. Modellen hade som indata en ordnad ström av sedda filmer. En extra ingångsvariabel, datumet för visualiseringen, gav en ökning av prestandan, som var mer märkbar i de kluster med färre filmer och fler visualiseringar, dvs. de kluster som inte motsvarade de minst populära klustren. Tillägget av en extra variabel, procent av filmen som har setts, gav inte entydiga resultat på grund av hårdvarubegränsningar / Desde hace más de 4 años, se está librando una lucha encarnizada por mantenerse en cabeza en la llamada ”Guerra del Streaming”. La Covid-19 y su consiguiente confinamiento no han hecho más que empeorar la situación. En un mercado como éste, en el que el usuario se encuentra con demasiados servicios de vídeo en streaming entre los que elegir, retener a los clientes se convierte en una necesidad. Además, un catálogo extenso dificulta aún más la elección de una película por parte del usuario. Los sistemas de recomendación intentan facilitar esta tarea analizando las interacciones de los usuarios con la plataforma y predecir las películas que, a priori, se verán a continuación. Las Redes Neuronales han comenzado a implementarse como tecnología subyacente en el desarrollo de los sistemas de recomendación. Sin embargo, la mayoría de los servicios de streaming son víctimas de una distribución de películas muy desigual, en la que una pequeña fracción de sus contenidos es vista por la mayoría de sus usuarios, teniendo el resto de su catálogo un número muy inferior de visualizaciones. Este es el denominado problema de ”long-tail” que dificulta el modelo de clasificación. Para resolver este problema se implementó un modelo RNN. Siguiendo una estrategia de clasificación de expertos múltiples, en la que cada clasificador se centra en un único grupo específico de películas, agrupadas por popularidad. Estos clusters se crearon siguiendo el algoritmo de Jenks, agrupando las películas mediante minimización y maximización de la varianza entre grupos . Esta nueva implementación acabó superando a otros métodos de clustering, donde los clusters de películas de Jenks propuestos dieron mejores resultados para los modelos correspondientes. El modelo tenía como entrada un flujo ordenado de películas vistas. Una variable de entrada extra, la fecha de la visualización, dio un incremento en el rendimiento, siendo más notable en aquellos clusters con una menor cantidad de películas y más visualizaciones, es decir, aquellos clusters que no corresponden a los menos populares. La adición de una variable extra, el porcentaje de películas vistas, dio resultados no concluyentes debido a limitaciones hardware.