1,425 research outputs found

    Random Linear Network Coding for Wireless Layered Video Broadcast: General Design Methods for Adaptive Feedback-free Transmission

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    This paper studies the problem of broadcasting layered video streams over heterogeneous single-hop wireless networks using feedback-free random linear network coding (RLNC). We combine RLNC with unequal error protection (UEP) and our main purpose is twofold. First, to systematically investigate the benefits of UEP+RLNC layered approach in servicing users with different reception capabilities. Second, to study the effect of not using feedback, by comparing feedback-free schemes with idealistic full-feedback schemes. To these ends, we study `expected percentage of decoded frames' as a key content-independent performance metric and propose a general framework for calculation of this metric, which can highlight the effect of key system, video and channel parameters. We study the effect of number of layers and propose a scheme that selects the optimum number of layers adaptively to achieve the highest performance. Assessing the proposed schemes with real H.264 test streams, the trade-offs among the users' performances are discussed and the gain of adaptive selection of number of layers to improve the trade-offs is shown. Furthermore, it is observed that the performance gap between the proposed feedback-free scheme and the idealistic scheme is very small and the adaptive selection of number of video layers further closes the gap.Comment: 15 pages, 12 figures, 3 tables, Under 2nd round of review, IEEE Transactions on Communication

    Joint in-network video rate adaptation and measurement-based admission control: algorithm design and evaluation

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    The important new revenue opportunities that multimedia services offer to network and service providers come with important management challenges. For providers, it is important to control the video quality that is offered and perceived by the user, typically known as the quality of experience (QoE). Both admission control and scalable video coding techniques can control the QoE by blocking connections or adapting the video rate but influence each other's performance. In this article, we propose an in-network video rate adaptation mechanism that enables a provider to define a policy on how the video rate adaptation should be performed to maximize the provider's objective (e.g., a maximization of revenue or QoE). We discuss the need for a close interaction of the video rate adaptation algorithm with a measurement based admission control system, allowing to effectively orchestrate both algorithms and timely switch from video rate adaptation to the blocking of connections. We propose two different rate adaptation decision algorithms that calculate which videos need to be adapted: an optimal one in terms of the provider's policy and a heuristic based on the utility of each connection. Through an extensive performance evaluation, we show the impact of both algorithms on the rate adaptation, network utilisation and the stability of the video rate adaptation. We show that both algorithms outperform other configurations with at least 10 %. Moreover, we show that the proposed heuristic is about 500 times faster than the optimal algorithm and experiences only a performance drop of approximately 2 %, given the investigated video delivery scenario

    Understanding user experience of mobile video: Framework, measurement, and optimization

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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

    SVCEval-RA: an evaluation framework for adaptive scalable video streaming

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    [EN] Multimedia content adaption strategies are becoming increasingly important for effective video streaming over the actual heterogeneous networks. Thus, evaluation frameworks for adaptive video play an important role in the designing and deploying process of adaptive multimedia streaming systems. This paper describes a novel simulation framework for rate-adaptive video transmission using the Scalable Video Coding standard (H.264/SVC). Our approach uses feedback information about the available bandwidth to allow the video source to select the most suitable combination of SVC layers for the transmission of a video sequence. The proposed solution has been integrated into the network simulator NS-2 in order to support realistic network simulations. To demonstrate the usefulness of the proposed solution we perform a simulation study where a video sequence was transmitted over a three network scenarios. The experimental results show that the Adaptive SVC scheme implemented in our framework provides an efficient alternative that helps to avoid an increase in the network congestion in resource-constrained networks. Improvements in video quality, in terms of PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity Index) are also obtained.Castellanos Hernández, WE.; Guerri Cebollada, JC.; Arce Vila, P. (2017). SVCEval-RA: an evaluation framework for adaptive scalable video streaming. Multimedia Tools and Applications. 76(1):437-461. doi:10.1007/s11042-015-3046-yS437461761Akhshabi S, Begen AC, Dovrolis C (2011) An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP. In: Proceedings of the second annual ACM conference on Multimedia systems. ACM, pp 157–168Alabdulkarim MN, Rikli N-E (2012) QoS Provisioning for H.264/SVC Streams over Ad-Hoc ZigBee Networks Using Cross-Layer Design. In: 8th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). pp 1–8Birkos K, Tselios C, Dagiuklas T, Kotsopoulos S (2013) Peer selection and scheduling of H. 264 SVC video over wireless networks. In: Wireless Communications and Networking Conference (WCNC), 2013 IEEE. pp 1633–1638Castellanos W (2014) SVCEval-RA - An Evaluation Framework for Adaptive Scalable Video Streaming. In: SourceForge Project. http://sourceforge.net/projects/svceval-ra/ . Accessed 1 May 2015Castellanos W, Guerri JC, Arce P (2015) A QoS-aware routing protocol with adaptive feedback scheme for video streaming for mobile networks. Comput Commun. http://dx.doi.org/10.1016/j.comcom.2015.08.012Castellanos W, Arce P, Acelas P, Guerri JC (2012) Route Recovery Algorithm for QoS-Aware Routing in MANETs. Springer Berlin Heidelberg, Bilbao, pp. 81–93Chikkerur S, Sundaram V, Reisslein M, Karam LJ (2011) Objective video quality assessment methods: A classification, review, and performance comparison. Broadcast, IEEE Trans on 57:165–182Choupani R, Wong S, Tolun M (2014) Multiple description coding for SNR scalable video transmission over unreliable networks. Multimed Tools Appl 69:843–858. doi: 10.1007/s11042-012-1150-9CISCO Corp. (2014) Cisco Visual Networking Index Forecast and Methodology. In: White Paper. http://www.cisco.com/c/en/us/solutions/collateral/service-provider/ip-ngn-ip-next-generation-network/white_paper_c11-481360.pdf.Dai M, Zhang Y, Loguinov D (2009) A unified traffic model for MPEG-4 and H. 264 video traces. IEEE Trans Multimedia 11:1010–1023Detti A, Bianchi G, Pisa C, et al. (2009) SVEF: an open-source experimental evaluation framework for H.264 scalable video streaming. 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    Simulation and experimental testbed for adaptive video streaming in ad hoc networks

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    [EN] This paper presents a performance evaluation of the scalable video streaming over mobile ad hoc networks. In particular, we focus on the rate-adaptive method for streaming scalable video (H.264/SVC). For effective adaptation a new cross-layer routing protocol is introduced. This protocol provides an efficient algorithm for available bandwidth estimation. With this information, the video source adjusts its bit rate during the video transmission according to the network state. We also propose a free simulation framework that supports evaluation studies for scalable video streaming. The simulation experiments performed in this study involve the transmission of SVC streams with Medium Grain Scalability (MGS) as well as temporal scalability over different network scenarios. The results reveal that the rate-adaptive strategy helps avoid or reduce the congestion in MANETs obtaining a better quality in the received videos. Additionally, an actual ad hoc network was implemented using embedded devices (Raspberry Pi) in order to assess the performance of the proposed adaptive transmission mechanism in a real environment. Additional experiments were carried out prior to the implementation with the aim of characterizing the wireless medium and packet loss profile. Finally, the proposed approach shows an important reduction in energy consumption, as the study revealed.This paper was performed with the support of the National Secretary of Higher Education, Science, Technology and Innovation (SENESCYT)–Ecuador Government (scholarship 195-2012) and the Multimedia Communications Group (COMM) belong to the Institute of Telecommunications and Multimedia Applications (iTEAM)-Universitat Politècnica de València.Gonzalez-Martinez, SR.; Castellanos Hernández, WE.; Guzmán Castillo, PF.; Arce Vila, P.; Guerri Cebollada, JC. (2016). Simulation and experimental testbed for adaptive video streaming in ad hoc networks. Ad Hoc Networks. 52:89-105. https://doi.org/10.1016/j.adhoc.2016.07.007S891055

    Fair-RTT-DAS: A robust and efficient dynamic adaptive streaming over ICN

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    To sustain the adequate bandwidth demands over rapidly growing multimedia traffic and considering the effectiveness of Information-Centric Networking (ICN), recently, HTTP based Dynamic Adaptive Streaming (DASH) has been introduced over ICN, which significantly increases the network bandwidth utilisation. However, we identified that the inherent features of ICN also causes new vulnerabilities in the network. In this paper, we first propose a novel attack called as Bitrate Oscillation Attack (BOA), which exploits fundamental ICN characteristics: in-network caching and interest aggregation, to disrupt DASH functionality. In particular, the proposed attack forces the bitrate and resolution of video received by the attacked client to oscillate with high frequency and high amplitude during the streaming process. To detect and mitigate BOA, we design and implement a reactive countermeasure called Fair-RTT-DAS. Our solution ensures efficient bandwidth utilisation and improves the user perceived Quality of Experience (QoE) in the presence of varying content source locations. For this purpose, Fair-RTT-DAS consider DASH\u2019s two significant features: round-trip-time (RTT) and throughput fairness. In the presence of BOA in a network, our simulation results show an increase in the annoyance factor in user\u2019s spatial dimension, i.e., increase in oscillation frequency and amplitude. The results also show that our countermeasure significantly alleviates these adverse effects and makes dynamic adaptive streaming friendly to ICN\u2019s implicit features
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