Management of Digital Video Broadcasting Services in Open Delivery Platforms

The future of Digital Video Broadcasting (DVB) is moving towards solutions offering an efficient way of carrying interactive IP multimedia services over digital terrestrial broadcasting networks to handheld terminals. One of the most promising technologies is Digital Video Broadcasting-Handheld (DVB-H), at present under standardisation. Services deployed via this type of DVB technologies should enjoy reliability comparable to TV services and high quality standards. However, the market at present does not provide effective and economical solutions for the deployment of such services over multi-domain IP networks, due to their high level of unreliability. This paper focuses on service management, service level agreement (SLA) and network performance requirements of DVB-H services. Experimental results are presented concerning QoS sensitivity to network performance of DVB-H services delivered over a multi-domain IP network. Moreover, a solution for efficient and cost effective service management via QoS monitoring and control and network SLA design is proposed. The solution gives DVB-H operators the possibility of fully managing service QoS without being tied to third party operators

Estimation of the QoE for video streaming services based on facial expressions and gaze direction

As the multimedia technologies evolve, the need to control their quality becomes even more important making the Quality of Experience (QoE) measurements a key priority. Machine Learning (ML) can support this task providing models to analyse the information extracted by the multimedia. It is possible to divide the ML models applications in the following categories: 1) QoE modelling: ML is used to define QoE models which provide an output (e.g., perceived QoE score) for any given input (e.g., QoE influence factor). 2) QoE monitoring in case of encrypted traffic: ML is used to analyze passive traffic monitored data to obtain insight into degradations perceived by end-users. 3) Big data analytics: ML is used for the extraction of meaningful and useful information from the collected data, which can further be converted to actionable knowledge and utilized in managing QoE. The QoE estimation quality task can be carried out by using two approaches: the objective approach and subjective one. As the two names highlight, they are referred to the pieces of information that the model analyses. The objective approach analyses the objective features extracted by the network connection and by the used media. As objective parameters, the state-of-the-art shows different approaches that use also the features extracted by human behaviour. The subjective approach instead, comes as a result of the rating approach, where the participants were asked to rate the perceived quality using different scales. This approach had the problem of being a time-consuming approach and for this reason not all the users agree to compile the questionnaire. Thus the direct evolution of this approach is the ML model adoption. A model can substitute the questionnaire and evaluate the QoE, depending on the data that analyses. By modelling the human response to the perceived quality on multimedia, QoE researchers found that the parameters extracted from the users could be different, like Electroencephalogram (EEG), Electrocardiogram (ECG), waves of the brain. The main problem with these techniques is the hardware. In fact, the user must wear electrodes in case of ECG and EEG, and also if the obtained results from these methods are relevant, their usage in a real context could be not feasible. For this reason, my studies have been focused on the developing of a Machine Learning framework completely unobtrusively based on the Facial reactions

Context-awareness for ubiquitous media service delivery in next generation networks

Les récentes avancées technologiques permettent désormais la fabrication de terminaux mobiles de plus en plus compacts et dotés de plusieurs interfaces réseaux. Le nouveau modèle de consommation de médias se résume par le concept "Anytime, Anywhere, Any Device" et impose donc de nouvelles exigences en termes de déploiement de services ubiquitaires. Cependant la conception et le developpement de réseaux ubiquitaires et convergents de nouvelles générations soulèvent un certain nombre de défis techniques. Les standards actuels ainsi que les solutions commerciales pourraient être affectés par le manque de considération du contexte utilisateur. Le ressenti de l'utilisateur concernant certains services multimédia tels que la VoIP et l'IPTV dépend fortement des capacités du terminal et des conditions du réseau d'accès. Cela incite les réseaux de nouvelles générations à fournir des services ubiquitaires adaptés à l'environnement de l'utilisateur optimisant par la même occasion ses resources. L'IP Multimedia Subsystem (IMS) est une architecture de nouvelle génération qui centralise l'accès aux services et permet la convergence des réseaux fixe/mobile. Néanmoins, l'évolution de l'IMS est nécessaire sur les points suivants :- l'introduction de la sensibilité au contexte utilisateur et de la PQoS (Perceived QoS) : L'architecture IMS ne prend pas en compte l'environnement de l'utilisateur, ses préférences et ne dispose pas d'un méchanisme de gestion de PQOS. Pour s'assurer de la qualité fournit à l'utilisateur final, des informations sur l'environnement de l'utilisateur ainsi que ses préférences doivent transiter en cœur de réseau afin d'y être analysés. Ce traitement aboutit au lancement du service qui sera adapté et optimisé aux conditions observées. De plus pour le service d'IPTV, les caractéristiques spatio-temporelles de la vidéo influent de manière importante sur la PQoS observée côté utilisateur. L'adaptation des services multimédias en fonction de l'évolution du contexte utilisateur et de la nature de la vidéo diffusée assure une qualité d'expérience à l'utilisateur et optimise par la même occasion l'utilisation des ressources en cœur de réseau.- une solution de mobilité efficace pour les services conversationnels tels que la VoIP : Les dernières publications 3GPP fournissent deux solutions de mobilité: le LTE proposeMIP comme solution de mobilité alors que l'IMS définit une mobilité basée sur le protocoleapplicatif SIP. Ces standards définissent le système de signalisation mais ne s'avancent pas sur la gestion du flux média lors du changement d'interface réseau. La deuxième section introduit une étude comparative détaillée des solutions de mobilité dans les NGNs.Notre première contribution est la spécification de l'architecture globale de notre plateforme IMS sensible au contexte utilisateur réalisée au sein du projet Européen ADAMANTIUM. Nous détaillons tout d'abord le serveur MCMS intelligent placé dans la couche application de l'IMS. Cet élément récolte les informations de qualité de services à différents équipements réseaux et prend la décision d'une action sur l'un de ces équipements. Ensuite nous définissons un profil utilisateur permettant de décrire son environnement et de le diffuser en coeur de réseau. Une étude sur la prédiction de satisfaction utilisateur en fonction des paramètres spatio-temporels de la vidéo a été réalisée afin de connaître le débit idéal pour une PQoS désirée.Notre deuxième contribution est l'introduction d'une solution de mobilité adaptée aux services conversationnels (VoIP) tenant compte du contexte utilisateur. Notre solution s'intègre à l'architecture IMS existante de façon transparente et permet de réduire le temps de latence du handover. Notre solution duplique les paquets de VoIP sur les deux interfaces actives pendant le temps de la transition. Parallèlement, un nouvel algorithme de gestion de mémoire tampon améliore la qualité d'expérience pour le service de VoIP.The latest advances in technology have already defied Moore s law. Thanks to research and industry, hand-held devices are composed of high processing embedded systems enabling the consumption of high quality services. Furthermore, recent trends in communication drive users to consume media Anytime, Anywhere on Any Device via multiple wired and wireless network interfaces. This creates new demands for ubiquitous and high quality service provision management. However, defining and developing the next generation of ubiquitous and converged networks raise a number of challenges. Currently, telecommunication standards do not consider context-awareness aspects for network management and service provisioning. The experience felt by the end-user consuming for instance Voice over IP (VoIP) or Internet Protocol TeleVision (IPTV) services varies depending mainly on user preferences, device context and network resources. It is commonly held that Next Generation Network (NGN) should deliver personalized and effective ubiquitous services to the end user s Mobile Node (MN) while optimizing the network resources at the network operator side. IP Multimedia Subsystem (IMS) is a standardized NGN framework that unifies service access and allows fixed/mobile network convergence. Nevertheless IMS technology still suffers from a number of confining factors that are addressed in this thesis; amongst them are two main issues :The lack of context-awareness and Perceived-QoS (PQoS):-The existing IMS infrastructure does not take into account the environment of the user ,his preferences , and does not provide any PQoS aware management mechanism within its service provisioning control system. In order to ensure that the service satisfies the consumer, this information need to be sent to the core network for analysis. In order to maximize the end-user satisfaction while optimizing network resources, the combination of a user-centric network management and adaptive services according to the user s environment and network conditions are considered. Moreover, video content dynamics are also considered as they significantly impact on the deduced perceptual quality of IPTV services. -The lack of efficient mobility mechanism for conversational services like VoIP :The latest releases of Third Generation Partnership Project (3GPP) provide two types of mobility solutions. Long-Term Evolution (LTE) uses Mobile IP (MIP) and IMS uses Session Initiation Protocol (SIP) mobility. These standards are focusing on signaling but none of them define how the media should be scheduled in multi-homed devices. The second section introduces a detailed study of existing mobility solutions in NGNs. Our first contribution is the specification of the global context-aware IMS architecture proposed within the European project ADAptative Management of mediA distributioN based on saTisfaction orIented User Modeling (ADAMANTIUM). We introduce the innovative Multimedia Content Management System (MCMS) located in the application layer of IMS. This server combines the collected monitoring information from different network equipments with the data of the user profile and takes adaptation actions if necessary. Then, we introduce the User Profile (UP) management within the User Equipment (UE) describing the end-user s context and facilitating the diffusion of the end-user environment towards the IMS core network. In order to optimize the network usage, a PQoS prediction mechanism gives the optimal video bit-rate according to the video content dynamics. Our second contribution in this thesis is an efficient mobility solution for VoIP service within IMS using and taking advantage of user context. Our solution uses packet duplication on both active interfaces during handover process. In order to leverage this mechanism, a new jitter buffer algorithm is proposed at MN side to improve the user s quality of experience. Furthermore, our mobility solution integrates easily to the existing IMS platform.BORDEAUX1-Bib.electronique (335229901) / SudocSudocFranceF

Statistical priority-based uplink scheduling for M2M communications

Currently, the worldwide network is witnessing major efforts to transform it from being the Internet of humans only to becoming the Internet of Things (IoT). It is expected that Machine Type Communication Devices (MTCDs) will overwhelm the cellular networks with huge traffic of data that they collect from their environments to be sent to other remote MTCDs for processing thus forming what is known as Machine-to-Machine (M2M) communications. Long Term Evolution (LTE) and LTE-Advanced (LTE-A) appear as the best technology to support M2M communications due to their native IP support. LTE can provide high capacity, flexible radio resource allocation and scalability, which are the required pillars for supporting the expected large numbers of deployed MTCDs. Supporting M2M communications over LTE faces many challenges. These challenges include medium access control and the allocation of radio resources among MTCDs. The problem of radio resources allocation, or scheduling, originates from the nature of M2M traffic. This traffic consists of a large number of small data packets, with specific deadlines, generated by a potentially massive number of MTCDs. M2M traffic is therefore mostly in the uplink direction, i.e. from MTCDs to the base station (known as eNB in LTE terminology). These characteristics impose some design requirements on M2M scheduling techniques such as the need to use insufficient radio resources to transmit a huge amount of traffic within certain deadlines. This presents the main motivation behind this thesis work. In this thesis, we introduce a novel M2M scheduling scheme that utilizes what we term the “statistical priority” in determining the importance of information carried by data packets. Statistical priority is calculated based on the statistical features of the data such as value similarity, trend similarity and auto-correlation. These calculations are made and then reported by the MTCDs to the serving eNBs along with other reports such as channel state. Statistical priority is then used to assign priorities to data packets so that the scarce radio resources are allocated to the MTCDs that are sending statistically important information. This would help avoid exploiting limited radio resources to carry redundant or repetitive data which is a common situation in M2M communications. In order to validate our technique, we perform a simulation-based comparison among the main scheduling techniques and our proposed statistical priority-based scheduling technique. This comparison was conducted in a network that includes different types of MTCDs, such as environmental monitoring sensors, surveillance cameras and alarms. The results show that our proposed statistical priority-based scheduler outperforms the other schedulers in terms of having the least losses of alarm data packets and the highest rate in sending critical data packets that carry non-redundant information for both environmental monitoring and video traffic. This indicates that the proposed technique is the most efficient in the utilization of limited radio resources as compared to the other techniques

Quality of experience management for YouTube: clouds, FoG and the AquareYoum

Over the last decade, Quality of Experience (QoE) has become a new, central paradigm for understanding the quality of networks and services. In particular, the concept has attracted the interest of communication network and service providers, since being able to guarantee good QoE to customers provides an opportunity for differentiation. In this paper we investigate the potential as well as the implementation challenges of QoE management in the Internet. Using YouTube video streaming service as example, we discuss the different elements that are required for the realization of the paradigm-shift towards truly user-centric network orchestration. To this end, we elaborate QoE management requirements for two complementary network scenarios (wireless mesh Internet access networks vs. global Internet delivery) and provide a QoE model for YouTube taking into account impairments like stalling and initial delay. We present two YouTube QoE monitoring approaches operating on the network and the end user level. Finally, we demonstrate how QoE can be dynamically optimized in both network scenarios with two exemplary concepts, AquareYoum and FoG, respectively. Our results show how QoE management can truly improve the user experience while at the same time increase the efficiency of network resource allocation

Indicator Of Experince For Mobile Data Networks

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2013Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2013Bu çalışmada mobil veri şebekeleri için kullanıcıların yaşadıkları deneyim kalitesini ölçmek adına farklı bir metod önerilmektedir. Literatürde önerilen yöntemler ağırlıklı olarak kullanıcıların deneyimlerine ilişkin görüşlerinin anketler düzenlenerek alınması veya mobil cihazlara yerleştirilen akıllı yazılımlar ile deneyimlerin ölçülmesi şeklindedir. Bu sebeple yapılan çalışmalar örnek küme üzerinden deneyimin bütüne aitmiş gibi konumlandırılması esasına dayanmaktadır. Bu çalışmada bahsedilen yöntemlerden farklı olarak mobil şebekede bulunan sistemsel istatistiklerin kullanılması ve radyo şebekesinin deneyime etkisini hesaplayan bir modelin önerilmesiyle farklı bir hesaplama yöntemi önerilmektedir. Bu sayede sadece belli bir örnek küme değil, servisi deneyimleyen tüm kullanıcılar için bir sonuç elde etmek mümkün olmaktadır. Bu amaçla IoE kısaltması adı altında mobil veri servisleri kullanımlarında deneyimin başarısı ölçülebilir ve hesaplanabilir bir parametre ile ifade edilmiştir.In this study, introducing a new way of quality of experience calculation methodology is aimed. A new parameter, indicator of experience (IoE) has been introduced, which is a combination of quantised throughput and acceptability of the user for mobile internet service. Most QoE calculations use mobile client or user perception researches. Differently, network level statistics and radio network modeling is used to calculate IoE. This new approach is then compared with mobile client measurements in order to prove the usability of the approach.Yüksek LisansM.Sc

Análise de desempenho e do comportamento do utilizador em redes 3G

Mestrado em Electrónica e TelecomunicaçõesA Qualidade de Serviço (QoS) é uma preocupação para os operadores, mas devido à evolução da rede para um enorme número de serviços com requisistos diferentes, garantir uma boa QoS não é exatcamente sinónimo de utilizadores satisfeitos. A percepção da qualidade de serviço por parte dos utilizadores (QoE) garante aos operadores uma visão do grau de satisfação do utilizador final. O objectivo de uma boa QoS deve ser promover uma melhor QoE nos utilizadores. A QoE permite aos operadores saberem de que forma é que as condições da rede satisfazem as expectativas dos seus utilizadores em termos de confiança, disponibilidade, escalabilidade, velocidade, desempenho e eficiência. O objectivo deste trabalho é o desenvolvimento de mecanismos que permitam aos operadores analisarem ao mesmo tempo o comportamento dos utilizadores e o estado da rede em termos de qualidade numa determinada região. Com este tipo de informação disponível os operadores podem adaptar os mecanismos de QoS da rede de modo a prencherem na totalidade as expectativas do utilizador final numa determinada região.The Quality of Service (QoS) is already a major concern for operators, but things are changing and, although in many cases better QoS results in better Quality of Experience (QoE), fulfilling the required performance parameters is not a synonym of satisfied users. QoE conditions can immediate response on the user satisfaction and thus the goal of QoS assurance should be to promote a better QoE. This will give the operator a deeper sense of the contribution of network’s performance to the overall level of customer satisfaction in terms of reliability, availability, scalability, speed, accuracy and efficiency. The main goal of this work is to provide operators with mechanisms for end user behaviour analysis and at the same instant detailed network status. With this information operators know the end users behaviour in a certain region, know in detail network performance metrics and can adapt QoS mechanisms to fulfil end users expectations