Smart resource allocation for improving QoE in IP Multimedia Subsystems

[EN] IP Multimedia Subsystem (IMS) is a robust multimedia service. IMS becomes more important when delivering multimedia services. Multimedia service providers can benefit from IMS to ensure a good QoE (Quality of Experience) to their customers with minimal resources usage. In this paper, we propose an intelligent media distribution IMS system architecture for delivering video streaming. The system is based primarily on uploading a multimedia file to a server in the IMS. Later, other users can download the uploaded multimedia file from the IMS. In the system, we also provide the design of the heuristic decision methods and models based on probability distributions. Thus, our system takes into account the network parameters such as bandwidth, jitter, delay and packet loss that influence the QoE of the end -users. Moreover, we have considered the other parameters of the energy consumption such as CPU, RAM, temperature and number connected users that impact the result of the QoE. All these parameters are considered as input to our proposal management system. The measurements taken from the real test bench show the real performance and demonstrate the success of the system about ensuring the upload speed of the multimedia file, guaranteeing the QoE of end users and improving the energy efficiency of the IMS.This work has been partially supported by the "Ministerio de Ciencia e Innovation", through the "Plan Nacional de I+D+i 2008-2011" in the "Subprograma de Proyectos de Investigation Fundamental", project TEC2011-27516, and by the Polytechnic University of Valencia, though the PAID-15-11 multidisciplinary projects.Canovas Solbes, A.; Taha, M.; Lloret, J.; Tomás Gironés, J. (2018). Smart resource allocation for improving QoE in IP Multimedia Subsystems. Journal of Network and Computer Applications. 104:107-116. https://doi.org/10.1016/j.jnca.2017.12.020S10711610

Network Performance Criteria for Telecommunication Traffic Types driven by Quality of Experience

A common reason for changing the chosen service provider is the users\u27 perception of service. Quality of Experience (QoE) describes the end user\u27s perception of service while using it. A frequent cause of QoE degradation is inadequate traffic routing, where, other than throughput, selected routes do not satisfy minimum network requirements for the given service or services. In order to enable QoE-driven routing, per traffic type defined routing criteria are required. Our goal was to obtain those criteria for relevant services of a telecom operator. For the purpose of identifying services of interest, we first provide short results of user traffic analysis within the telecom operator network. Next, our work presents testbed measurements which explore the impact of packet loss and delay on user QoE for video, voice, and management traffic. For video services, we investigated separately multicast delivery, unicast HTTP Live Streaming (HLS), and unicast Real Time Streaming Protocol (RTSP) traffic. Applying a threshold to QoE values, from the measured dependencies we extracted minimum network performance criteria for the investigated different types of traffic. Finally, we provide a comparison with results available in the literature on the topic

Architecture and Protocol to Optimize Videoconference in Wireless Networks

[EN] In the past years, videoconferencing (VC) has become an essential means of communications. VC allows people to communicate face to face regardless of their location, and it can be used for different purposes such as business meetings, medical assistance, commercial meetings, and military operations. There are a lot of factors in real-time video transmission that can affect to the quality of service (QoS) and the quality of experience (QoE). The application that is used (Adobe Connect, Cisco Webex, and Skype), the internet connection, or the network used for the communication can affect to the QoE. Users want communication to be as good as possible in terms of QoE. In this paper, we propose an architecture for videoconferencing that provides better quality of experience than other existing applications such as Adobe Connect, Cisco Webex, and Skype. We will test how these three applications work in terms of bandwidth, packets per second, and delay using WiFi and 3G/4G connections. Finally, these applications are compared to our prototype in the same scenarios as they were tested, and also in an SDN, in order to improve the advantages of the prototype.This work has been supported by the "Ministerio de Economia y Competitividad" in the "Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia, Subprograma Estatal de Generacion de Conocimiento" within the project under Grant TIN2017-84802-C2-1-P.Jimenez, JM.; García-Navas, JL.; Lloret, J.; Romero Martínez, JO. (2020). Architecture and Protocol to Optimize Videoconference in Wireless Networks. Wireless Communications and Mobile Computing. 2020:1-22. https://doi.org/10.1155/2020/4903420S122202

Computational inference and control of quality in multimedia services

Quality is the degree of excellence we expect of a service or a product. It is also one of the key factors that determine its value. For multimedia services, understanding the experienced quality means understanding how the delivered delity, precision and reliability correspond to the users' expectations. Yet the quality of multimedia services is inextricably linked to the underlying technology. It is developments in video recording, compression and transport as well as display technologies that enables high quality multimedia services to become ubiquitous. The constant evolution of these technologies delivers a steady increase in performance, but also a growing level of complexity. As new technologies stack on top of each other the interactions between them and their components become more intricate and obscure. In this environment optimizing the delivered quality of multimedia services becomes increasingly challenging. The factors that aect the experienced quality, or Quality of Experience (QoE), tend to have complex non-linear relationships. The subjectively perceived QoE is hard to measure directly and continuously evolves with the user's expectations. Faced with the diculty of designing an expert system for QoE management that relies on painstaking measurements and intricate heuristics, we turn to an approach based on learning or inference. The set of solutions presented in this work rely on computational intelligence techniques that do inference over the large set of signals coming from the system to deliver QoE models based on user feedback. We furthermore present solutions for inference of optimized control in systems with no guarantees for resource availability. This approach oers the opportunity to be more accurate in assessing the perceived quality, to incorporate more factors and to adapt as technology and user expectations evolve. In a similar fashion, the inferred control strategies can uncover more intricate patterns coming from the sensors and therefore implement farther-reaching decisions. Similarly to natural systems, this continuous adaptation and learning makes these systems more robust to perturbations in the environment, longer lasting accuracy and higher eciency in dealing with increased complexity. Overcoming this increasing complexity and diversity is crucial for addressing the challenges of future multimedia system. Through experiments and simulations this work demonstrates that adopting an approach of learning can improve the sub jective and objective QoE estimation, enable the implementation of ecient and scalable QoE management as well as ecient control mechanisms

Otimização de distribuição de conteúdos multimédia utilizando software-defined networking

The general use of Internet access and user equipments, such as smartphones, tablets and personal computers, is creating a new wave of video content consumption. In the past two decades, the Television broadcasting industry went through several evolutions and changes, evolving from analog to digital distribution, standard definition to high definition TV-channels, form the IPTV method of distribution to the latest set of technologies in content distribution, OTT. The IPTV technology introduced features that changed the passive role of the client to an active one, revolutionizing the way users consume TV content. Thus, the clients’ habits started to shape the services offered, leading to an anywhere and anytime offer of video content. OTT video delivery is a reflection of those habits, meeting the users’ desire, introducing several benefits discussed in this work over the previous technologies. However, the OTT type of delivery poses several challenges in terms of scalability and threatens the Telecommunications Operators business model, because OTT companies use the Telcos infrastructure for free. Consequently, Telecommunications Operators must prepare their infrastructure for future demand while offering new services to stay competitive. This dissertation aims to contribute with insights on what infrastructure changes a Telecommunications Operator must perform with a proposed bandwidth forecasting model. The results obtained from the forecast model paved the way to the proposed video content delivery method, which aims to improve users’ perceived Quality-of-Experience while optimizing load balancing decisions. The overall results show an improvement of users’ experience using the proposed method.A generalização do acesso à Internet e equipamentos pessoais como smartphones, tablets e computadores pessoais, está a criar uma nova onda de consumo de conteúdos multimedia. Nas ultimas duas décadas, a indústria de transmissão de Televisão atravessou várias evoluções e alterações, evoluindo da distribuição analógica para a digital, de canais de Televisão de definição padrão para alta definição, do método de distribuição IPTV, até ao último conjunto de tecnologias na distribuição de conteúdos, OTT. A tecnologia IPTV introduziu novas funcionalidades que mudaram o papel passivo do cliente para um papel activo, revolucionando a forma como os utilizadores consumem conteúdos televisivos. Assim, os hábitos dos clientes começaram a moldar os serviços oferecidos, levando à oferta de consumo de conteúdos em qualquer lugar e em qualquer altura. A entrega de vídeo OTT é um reflexo destes hábitos, indo ao encontro dos desejos dos utilizadores, que introduz inúmeras vantagens sobre outras tecnologias discutidas neste trabalho. No entanto, a entrega de conteúdos OTT cria diversos problemas de escalabilidade e ameaça o modelo de negócio das Operadoras de Telecomunicações, porque os fornecedores de serviço OTT usam a infraestrutura das mesmas sem quaisquer custos. Consequentemente, os Operadores de Telecomunicações devem preparar a sua infraestrutura para o consumo futuro ao mesmo tempo que oferecem novos serviços para se manterem competitivos. Esta dissertação visa contribuir com conhecimento sobre quais alterações uma Operadora de Telecomunicações deve executar com o modelo de previsão de largura de banda proposto. Os resultados obtidos abriram caminho para o método de entrega de conteúdos multimedia proposto, que visa ao melhoramento da qualidade de experiência do utilizador ao mesmo tempo que se optimiza o processo de balanceamento de carga. No geral os testes confirmam uma melhoria na qualidade de experiência do utilizador usando o método proposto.Mestrado em Engenharia de Computadores e Telemátic

A QoE adaptive management system for high definition video streaming over wireless networks

[EN] The development of the smart devices had led to demanding high-quality streaming videos over wireless communications. In Multimedia technology, the Ultra-High Definition (UHD) video quality has an important role due to the smart devices that are capable of capturing and processing high-quality video content. Since delivery of the high-quality video stream over the wireless networks adds challenges to the end-users, the network behaviors 'factors such as delay of arriving packets, delay variation between packets, and packet loss, are impacted on the Quality of Experience (QoE). Moreover, the characteristics of the video and the devices are other impacts, which influenced by the QoE. In this research work, the influence of the involved parameters is studied based on characteristics of the video, wireless channel capacity, and receivers' aspects, which collapse the QoE. Then, the impact of the aforementioned parameters on both subjective and objective QoE is studied. A smart algorithm for video stream services is proposed to optimize assessing and managing the QoE of clients (end-users). The proposed algorithm includes two approaches: first, using the machine-learning model to predict QoE. Second, according to the QoE prediction, the algorithm manages the video quality of the end-users by offering better video quality. As a result, the proposed algorithm which based on the least absolute shrinkage and selection operator (LASSO) regression is outperformed previously proposed methods for predicting and managing QoE of streaming video over wireless networks.This work has been partially supported by the "Ministerio de Economia y Competitividad" in the "Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia, Subprograma Estatal de Generacion de Conocimiento" with in the Project under Grant TIN2017-84802-C2-1-P. This study has been partially done in the computer science departments at the (University of Sulaimani and Halabja).Taha, M.; Canovas, A.; Lloret, J.; Ali, A. (2021). A QoE adaptive management system for high definition video streaming over wireless networks. Telecommunication Systems. 77(1):63-81. https://doi.org/10.1007/s11235-020-00741-2638177