75 resultados para QoE


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A real-time adaptive resource allocation algorithm considering the end user's Quality of Experience (QoE) in the context of video streaming service is presented in this work. An objective no-reference quality metric, namely Pause Intensity (PI), is used to control the priority of resource allocation to users during the scheduling process. An online adjustment has been introduced to adaptively set the scheduler's parameter and maintain a desired trade-off between fairness and efficiency. The correlation between the data rates (i.e. video code rates) demanded by users and the data rates allocated by the scheduler is taken into account as well. The final allocated rates are determined based on the channel status, the distribution of PI values among users, and the scheduling policy adopted. Furthermore, since the user's capability varies as the environment conditions change, the rate adaptation mechanism for video streaming is considered and its interaction with the scheduling process under the same PI metric is studied. The feasibility of implementing this algorithm is examined and the result is compared with the most commonly existing scheduling methods.

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A framework that aims to best utilize the mobile network resources for video applications is presented in this paper. The main contribution of the work proposed is the QoE-driven optimization method that can maintain a desired trade-off between fairness and efficiency in allocating resources in terms of data rates to video streaming users in LTE networks. This method is concerned with the control of the user satisfaction level from the service continuity's point of view and applies appropriate QoE metrics (Pause Intensity and variations) to determine the scheduling strategies in combination with the mechanisms used for adaptive video streaming such as 3GP/MPEG-DASH. The superiority of the proposed algorithms are demonstrated, showing how the resources of a mobile network can be optimally utilized by using quantifiable QoE measurements. This approach can also find the best match between demand and supply in the process of network resource distribution.

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Mobile WiFi devices are becoming increasingly popular in non-seamless and user-controlled mobile traffic offloading alongside the standard WiFi hotspots. Unlike the operator-controlled hotspots, a mobile WiFi device relies on the capacity of the macro-cell for the data rate allocated to it. This type of devices can help offloading data traffic from the macro-cell base station and serve the end users within a closer range, but will change the pattern of resource distributions operated by the base station. We propose a resource allocation scheme that aims to optimize user quality of experience (QoE) when accessing video services in the environment where traffic offloading is taking place through interworking between a mobile communication system and low range wireless LANs. In this scheme, a rate redistribution algorithm is derived to perform scheduling which is controlled by a no-reference quality assessment metric in order to achieve the desired trade-offs between efficiency and fairness. We show the performance of this algorithm in terms of the distribution of the allocated data rates throughout the macro-cell investigated and the service coverage offered by the WiFi access point.

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A segment selection method controlled by Quality of Experience (QoE) factors for Dynamic Adaptive Streaming over HTTP (DASH) is presented in this paper. Current rate adaption algorithms aim to eliminate buffer underrun events by significantly reducing the code rate when experiencing pauses in replay. In reality, however, viewers may choose to accept a level of buffer underrun in order to achieve an improved level of picture fidelity or to accept the degradation in picture fidelity in order to maintain the service continuity. The proposed rate adaption scheme in our work can maximize the user QoE in terms of both continuity and fidelity (picture quality) in DASH applications. It is shown that using this scheme a high level of quality for streaming services, especially at low packet loss rates, can be achieved. Our scheme can also maintain a best trade-off between continuity-based quality and fidelity-based quality, by determining proper threshold values for the level of quality intended by clients with different quality requirements. In addition, the integration of the rate adaptation mechanism with the scheduling process is investigated in the context of a mobile communication network and related performances are analyzed.

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Mobile communication and networking infrastructures play an important role in the development of smart cities, to support real-time information exchange and management required in modern urbanization. Mobile WiFi devices that help offloading data traffic from the macro-cell base station and serve the end users within a closer range can significantly improve the connectivity of wireless communications between essential components including infrastructural and human devices in a city. However, this offloading function through interworking between LTE and WiFi systems will change the pattern of resource distributions operated by the base station. In this paper, a resource allocation scheme is proposed to ensure stable service coverage and end-user quality of experience (QoE) when offloading takes place in a macro-cell environment. In this scheme, a rate redistribution algorithm is derived to form a parametric scheduler to meet the required levels of efficiency and fairness, guided by a no-reference quality assessment metric. We show that the performance of resource allocation can be regulated by this scheduler without affecting the service coverage offered by the WLAN access point. The performances of different interworking scenarios and macro-cell scheduling policies are also compared.

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Frequency, time and places of charging and discharging have critical impact on the Quality of Experience (QoE) of using Electric Vehicles (EVs). EV charging and discharging scheduling schemes should consider both the QoE of using EV and the load capacity of the power grid. In this paper, we design a traveling plan-aware scheduling scheme for EV charging in driving pattern and a cooperative EV charging and discharging scheme in parking pattern to improve the QoE of using EV and enhance the reliability of the power grid. For traveling planaware scheduling, the assignment of EVs to Charging Stations (CSs) is modeled as a many-to-one matching game and the Stable Matching Algorithm (SMA) is proposed. For cooperative EV charging and discharging in parking pattern, the electricity exchange between charging EVs and discharging EVs in the same parking lot is formulated as a many-to-many matching model with ties, and we develop the Pareto Optimal Matching Algorithm (POMA). Simulation results indicates that the SMA can significantly improve the average system utility for EV charging in driving pattern, and the POMA can increase the amount of electricity offloaded from the grid which is helpful to enhance the reliability of the power grid.

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Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the user’s interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining users’ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account user’s needs and desires when using the service, emphasizing the user’s overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study.

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The increasing demand for mobile video has attracted much attention from both industry and researchers. To satisfy users and to facilitate the usage of mobile video, providing optimal quality to the users is necessary. As a result, quality of experience (QoE) becomes an important focus in measuring the overall quality perceived by the end-users, from the aspects of both objective system performance and subjective experience. However, due to the complexity of user experience and diversity of resources (such as videos, networks and mobile devices), it is still challenging to develop QoE models for mobile video that can represent how user-perceived value varies with changing conditions. Previous QoE modelling research has two main limitations: aspects influencing QoE are insufficiently considered; and acceptability as the user value is seldom studied. Focusing on the QoE modelling issues, two aims are defined in this thesis: (i) investigating the key influencing factors of mobile video QoE; and (ii) establishing QoE prediction models based on the relationships between user acceptability and the influencing factors, in order to help provide optimal mobile video quality. To achieve the first goal, a comprehensive user study was conducted. It investigated the main impacts on user acceptance: video encoding parameters such as quantization parameter, spatial resolution, frame rate, and encoding bitrate; video content type; mobile device display resolution; and user profiles including gender, preference for video content, and prior viewing experience. Results from both quantitative and qualitative analysis revealed the significance of these factors, as well as how and why they influenced user acceptance of mobile video quality. Based on the results of the user study, statistical techniques were used to generate a set of QoE models that predict the subjective acceptability of mobile video quality by using a group of the measurable influencing factors, including encoding parameters and bitrate, content type, and mobile device display resolution. Applying the proposed QoE models into a mobile video delivery system, optimal decisions can be made for determining proper video coding parameters and for delivering most suitable quality to users. This would lead to consistent user experience on different mobile video content and efficient resource allocation. The findings in this research enhance the understanding of user experience in the field of mobile video, which will benefit mobile video design and research. This thesis presents a way of modelling QoE by emphasising user acceptability of mobile video quality, which provides a strong connection between technical parameters and user-desired quality. Managing QoE based on acceptability promises the potential for adapting to the resource limitations and achieving an optimal QoE in the provision of mobile video content.

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The key requirements for enabling real-time remote healthcare service on a mobile platform, in the present day heterogeneous wireless access network environment, are uninterrupted and continuous access to the online patient vital medical data, monitor the physical condition of the patient through video streaming, and so on. For an application, this continuity has to be sufficiently transparent both from a performance perspective as well as a Quality of Experience (QoE) perspective. While mobility protocols (MIPv6, HIP, SCTP, DSMIP, PMIP, and SIP) strive to provide both and do so, limited or non-availability (deployment) of these protocols on provider networks and server side infrastructure has impeded adoption of mobility on end user platforms. Add to this, the cumbersome OS configuration procedures required to enable mobility protocol support on end user devices and the user's enthusiasm to add this support is lost. Considering the lack of proper mobility implementations that meet the remote healthcare requirements above, we propose SeaMo+ that comprises a light-weight application layer framework, termed as the Virtual Real-time Multimedia Service (VRMS) for mobile devices to provide an uninterrupted real-time multimedia information access to the mobile user. VRMS is easy to configure, platform independent, and does not require additional network infrastructure unlike other existing schemes. We illustrate the working of SeaMo+ in two realistic remote patient monitoring application scenarios.

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[ES]El objetivo principal de este trabajo es el diseño y desarrollo de un sistema para la validación de las metodologías propuestas en el borrador de recomendación P.STMWeb [1] “Metodología para la evaluación subjetiva de la calidad percibida en la navegación web”. Como resultado de la validación realizada con el sistema han sido aprobadas las recomendaciones G.1031 [5] “Factores del QoE en web browsing” y P.1501 [6] “Metodología de prueba subjetiva para web browsing” de la ITU-T. El sistema propuesto se ha diseñado en base a las especificaciones marcadas en el borrador de la recomendación en vías de estandarización [P.STMWeb].Estas especificaciones han servido de base para el diseño e implementación de un sistema que permite una navegación web interactiva, con control y actualización de páginas web en base a variaciones de parámetros de red, como el retardo en un entorno controlado. Así mismo siguiendo la metodología establecida en el borrador de recomendación anteriormente mencionado se ha diseñado y desarrollado un sistema de encuestas para evaluar de forma subjetiva la calidad experimentada por los usuarios (QoE) en la navegación web. Para el diseño del sistema de encuestas, se analizaron y utilizaron como especificaciones los diferentes factores que se contemplan en el borrador de recomendación G.QoE-Web [2] “Factores relevantes y casos de uso para la QoE Web” de la ITU-T. En base al diseño realizado, se ha desarrollado un sistema que permite analizar la calidad experimentada por los usuarios en la navegación Web.

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The proliferation problem of video streaming applications and mobile devices has prompted wireless network operators to put more efforts into improving quality of experience (QoE) while saving resources that are needed for high transmission rate and large size of video streaming. To deal with this problem, we propose an energy-aware rate and description allocation optimization method for video streaming in cellular network assisted device-to-device (D2D) communications. In particular, we allocate the optimal bit rate to each layer of video segments and packetize the segments into multiple descriptions with embedded forward error correction (FEC) for realtime streaming without retransmission. Simultaneously, the optimal number of descriptions is allocated to each D2D helper for transmission. The two allocation processes are done according to the access rate of segments, channel state information (CSI) of D2D requester, and remaining energy of helpers, to gain the highest optimization performance. Simulation results demonstrate that our proposed method (named OPT) significantly enhances the performance of video streaming in terms of high QoE and energy saving.

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Nowadays, communication environments are already characterized by a myriad of competing and complementary technologies that aim to provide an ubiquitous connectivity service. Next Generation Networks need to hide this heterogeneity by providing a new abstraction level, while simultaneously be aware of the underlying technologies to deliver richer service experiences to the end-user. Moreover, the increasing interest for group-based multimedia services followed by their ever growing resource demands and network dynamics, has been boosting the research towards more scalable and exible network control approaches. The work developed in this Thesis enables such abstraction and exploits the prevailing heterogeneity in favor of a context-aware network management and adaptation. In this scope, we introduce a novel hierarchical control framework with self-management capabilities that enables the concept of Abstract Multiparty Trees (AMTs) to ease the control of multiparty content distribution throughout heterogeneous networks. A thorough evaluation of the proposed multiparty transport control framework was performed in the scope of this Thesis, assessing its bene ts in terms of network selection, delivery tree recon guration and resource savings. Moreover, we developed an analytical study to highlight the scalability of the AMT concept as well as its exibility in large scale networks and group sizes. To prove the feasibility and easy deployment characteristic of the proposed control framework, we implemented a proof-of-concept demonstrator that comprehends the main control procedures conceptually introduced. Its outcomes highlight a good performance of the multiparty content distribution tree control, including its local and global recon guration. In order to endow the AMT concept with the ability to guarantee the best service experience by the end-user, we integrate in the control framework two additional QoE enhancement approaches. The rst employs the concept of Network Coding to improve the robustness of the multiparty content delivery, aiming at mitigating the impact of possible packet losses in the end-user service perception. The second approach relies on a machine learning scheme to autonomously determine at each node the expected QoE towards a certain destination. This knowledge is then used by di erent QoE-aware network management schemes that, jointly, maximize the overall users' QoE. The performance and scalability of the control procedures developed, aided by the context and QoE-aware mechanisms, show the advantages of the AMT concept and the proposed hierarchical control strategy for the multiparty content distribution with enhanced service experience. Moreover we also prove the feasibility of the solution in a practical environment, and provide future research directions that bene t the evolved control framework and make it commercially feasible.

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Web services from different partners can be combined to applications that realize a more complex business goal. Such applications built as Web service compositions define how interactions between Web services take place in order to implement the business logic. Web service compositions not only have to provide the desired functionality but also have to comply with certain Quality of Service (QoS) levels. Maximizing the users' satisfaction, also reflected as Quality of Experience (QoE), is a primary goal to be achieved in a Service-Oriented Architecture (SOA). Unfortunately, in a dynamic environment like SOA unforeseen situations might appear like services not being available or not responding in the desired time frame. In such situations, appropriate actions need to be triggered in order to avoid the violation of QoS and QoE constraints. In this thesis, proper solutions are developed to manage Web services and Web service compositions with regard to QoS and QoE requirements. The Business Process Rules Language (BPRules) was developed to manage Web service compositions when undesired QoS or QoE values are detected. BPRules provides a rich set of management actions that may be triggered for controlling the service composition and for improving its quality behavior. Regarding the quality properties, BPRules allows to distinguish between the QoS values as they are promised by the service providers, QoE values that were assigned by end-users, the monitored QoS as measured by our BPR framework, and the predicted QoS and QoE values. BPRules facilitates the specification of certain user groups characterized by different context properties and allows triggering a personalized, context-aware service selection tailored for the specified user groups. In a service market where a multitude of services with the same functionality and different quality values are available, the right services need to be selected for realizing the service composition. We developed new and efficient heuristic algorithms that are applied to choose high quality services for the composition. BPRules offers the possibility to integrate multiple service selection algorithms. The selection algorithms are applicable also for non-linear objective functions and constraints. The BPR framework includes new approaches for context-aware service selection and quality property predictions. We consider the location information of users and services as context dimension for the prediction of response time and throughput. The BPR framework combines all new features and contributions to a comprehensive management solution. Furthermore, it facilitates flexible monitoring of QoS properties without having to modify the description of the service composition. We show how the different modules of the BPR framework work together in order to execute the management rules. We evaluate how our selection algorithms outperform a genetic algorithm from related research. The evaluation reveals how context data can be used for a personalized prediction of response time and throughput.

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Context-aware multimodal interactive systems aim to adapt to the needs and behavioural patterns of users and offer a way forward for enhancing the efficacy and quality of experience (QoE) in human-computer interaction. The various modalities that constribute to such systems each provide a specific uni-modal response that is integratively presented as a multi-modal interface capable of interpretation of multi-modal user input and appropriately responding to it through dynamically adapted multi-modal interactive flow management , This paper presents an initial background study in the context of the first phase of a PhD research programme in the area of optimisation of data fusion techniques to serve multimodal interactivite systems, their applications and requirements.

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A Internet atual vem sofrendo vários problemas em termos de escalabilidade, desempenho, mobilidade, etc., devido ao vertiginoso incremento no número de usuários e o surgimento de novos serviços com novas demandas, propiciando assim o nascimento da Internet do Futuro. Novas propostas sobre redes orientadas a conteúdo, como a arquitetura Entidade Titulo (ETArch), proveem novos serviços para este tipo de cenários, implementados sobre o paradigma de redes definidas por software. Contudo, o modelo de transporte do ETArch é equivalente ao modelo best-effort da Internet atual, e vem limitando a confiabilidade das suas comunicações. Neste trabalho, ETArch é redesenhado seguindo o paradigma do sobreaprovisionamento de recursos para conseguir uma alocação de recursos avançada integrada com OpenFlow. Como resultado, o framework SMART (Suporte de Sessões Móveis com Alta Demanda de Recursos de Transporte), permite que a rede defina semanticamente os requisitos qualitativos das sessões para assim gerenciar o controle de Qualidade de Serviço visando manter a melhor Qualidade de Experiência possível. A avaliação do planos de dados e de controle teve lugar na plataforma de testes na ilha do projeto OFELIA, mostrando o suporte de aplicações móveis multimídia com alta demanda de recursos de transporte com QoS e QoE garantidos através de um esquema de sinalização restrito em comparação com o ETArch legado