44 research outputs found

    Modeling And Dynamic Resource Allocation For High Definition And Mobile Video Streams

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    Video streaming traffic has been surging in the last few years, which has resulted in an increase of its Internet traffic share on a daily basis. The importance of video streaming management has been emphasized with the advent of High Definition: HD) video streaming, as it requires by its nature more network resources. In this dissertation, we provide a better support for managing HD video traffic over both wireless and wired networks through several contributions. We present a simple, general and accurate video source model: Simplified Seasonal ARIMA Model: SAM). SAM is capable of capturing the statistical characteristics of video traces with less than 5% difference from their calculated optimal models. SAM is shown to be capable of modeling video traces encoded with MPEG-4 Part2, MPEG-4 Part10, and Scalable Video Codec: SVC) standards, using various encoding settings. We also provide a large and publicly-available collection of HD video traces along with their analyses results. These analyses include a full statistical analysis of HD videos, in addition to modeling, factor and cluster analyses. These results show that by using SAM, we can achieve up to 50% improvement in video traffic prediction accuracy. In addition, we developed several video tools, including an HD video traffic generator based on our model. Finally, to improve HD video streaming resource management, we present a SAM-based delay-guaranteed dynamic resource allocation: DRA) scheme that can provide up to 32.4% improvement in bandwidth utilization

    4K video traffic prediction using seasonal autoregressive modeling

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    On Transmission System Design for Wireless Broadcasting

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    This thesis considers aspects related to the design and standardisation of transmission systems for wireless broadcasting, comprising terrestrial and mobile reception. The purpose is to identify which factors influence the technical decisions and what issues could be better considered in the design process in order to assess different use cases, service scenarios and end-user quality. Further, the necessity of cross-layer optimisation for efficient data transmission is emphasised and means to take this into consideration are suggested. The work is mainly related terrestrial and mobile digital video broadcasting systems but many of the findings can be generalised also to other transmission systems and design processes. The work has led to three main conclusions. First, it is discovered that there are no sufficiently accurate error criteria for measuring the subjective perceived audiovisual quality that could be utilised in transmission system design. Means for designing new error criteria for mobile TV (television) services are suggested and similar work related to other services is recommended. Second, it is suggested that in addition to commercial requirements there should be technical requirements setting the frame work for the design process of a new transmission system. The technical requirements should include the assessed reception conditions, technical quality of service and service functionalities. Reception conditions comprise radio channel models, receiver types and antenna types. Technical quality of service consists of bandwidth, timeliness and reliability. Of these, the thesis focuses on radio channel models and errorcriteria (reliability) as two of the most important design challenges and provides means to optimise transmission parameters based on these. Third, the thesis argues that the most favourable development for wireless broadcasting would be a single system suitable for all scenarios of wireless broadcasting. It is claimed that there are no major technical obstacles to achieve this and that the recently published second generation digital terrestrial television broadcasting system provides a good basis. The challenges and opportunities of a universal wireless broadcasting system are discussed mainly from technical but briefly also from commercial and regulatory aspectSiirretty Doriast

    Prediction of Quality of Experience for Video Streaming Using Raw QoS Parameters

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    Along with the rapid growth in consumer adoption of modern portable devices, video streaming is expected to dominate a large share of the global Internet traffic in the near future. Today user experience is becoming a reliable indicator for video service providers and telecommunication operators to convey overall end-to-end system functioning. Towards this, there is a profound need for an efficient Quality of Experience (QoE) monitoring and prediction. QoE is a subjective metric, which deals with user perception and can vary due to the user expectation and context. However, available QoE measurement techniques that adopt a full reference method are impractical in real-time transmission since they require the original video sequence to be available at the receiver’s end. QoE prediction, however, requires a firm understanding of those Quality of Service (QoS) factors that are the most influential on QoE. The main aim of this thesis work is the development of novel and efficient models for video quality prediction in a non-intrusive way and to demonstrate their application in QoE-enabled optimisation schemes for video delivery. In this thesis, the correlation between QoS and QoE is utilized to objectively estimate the QoE. For this, both objective and subjective methods were used to create datasets that represent the correlation between QoS parameters and measured QoE. Firstly, the impact of selected QoS parameters from both encoding and network levels on video QoE is investigated. The obtained QoS/QoE correlation is backed by thorough statistical analysis. Secondly, the development of two novel hybrid non-reference models for predicting video quality using fuzzy logic inference systems (FIS) as a learning-based technique. Finally, attention was move onto demonstrating two applications of the developed FIS prediction model to show how QoE is used to optimise video delivery

    Video Caching, Analytics and Delivery at the Wireless Edge: A Survey and Future Directions

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    Future wireless networks will provide high bandwidth, low-latency, and ultra-reliable Internet connectivity to meet the requirements of different applications, ranging from mobile broadband to the Internet of Things. To this aim, mobile edge caching, computing, and communication (edge-C3) have emerged to bring network resources (i.e., bandwidth, storage, and computing) closer to end users. Edge-C3 allows improving the network resource utilization as well as the quality of experience (QoE) of end users. Recently, several video-oriented mobile applications (e.g., live content sharing, gaming, and augmented reality) have leveraged edge-C3 in diverse scenarios involving video streaming in both the downlink and the uplink. Hence, a large number of recent works have studied the implications of video analysis and streaming through edge-C3. This article presents an in-depth survey on video edge-C3 challenges and state-of-the-art solutions in next-generation wireless and mobile networks. Specifically, it includes: a tutorial on video streaming in mobile networks (e.g., video encoding and adaptive bitrate streaming); an overview of mobile network architectures, enabling technologies, and applications for video edge-C3; video edge computing and analytics in uplink scenarios (e.g., architectures, analytics, and applications); and video edge caching, computing and communication methods in downlink scenarios (e.g., collaborative, popularity-based, and context-aware). A new taxonomy for video edge-C3 is proposed and the major contributions of recent studies are first highlighted and then systematically compared. Finally, several open problems and key challenges for future research are outlined

    QoE management of HTTP adaptive streaming services

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