13,311 research outputs found

    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. In: IEEE Symposium on Computers and Communications. pp 36–41Espina F, Morato D, Izal M, Magaña E (2014) Analytical model for MPEG video frame loss rates and playback interruptions on packet networks. Multimed Tools Appl 72:361–383. doi: 10.1007/s11042-012-1344-1Fiems D, Steyaert B, Bruneel H (2012) A genetic approach to Markovian characterisation of H.264 scalable video. Multimedia Tools Appl 58:125–146Floyd S, Handley M, Kohler E Datagram Congestion Control Protocol (DCCP). http://tools.ietf.org/html/rfc4340 . Accessed 17 Feb 2014Floyd S, Padhye J, Widmer J TCP Friendly Rate Control (TFRC): Protocol Specification. http://tools.ietf.org/html/rfc5348 . Accessed 17 Feb 2014Fraz M, Malkani YA, Elahi MA (2009) Design and implementation of real time video streaming and ROI transmission system using RTP on an embedded digital signal processing (DSP) platform. In: 2nd International Conference on Computer, Control and Communication, 2009. IC4 2009. pp 1–6ISO/IEC (2014) Information technology - Dynamic adaptive streaming over HTTP (DASH) - Part 1: Media presentation description and segment formats.ITU-T (2013) Rec. H.264 & ISO/IEC 14496-10 AVC. Advanced Video Coding for Generic Audiovisual Services.Ivrlač MT, Choi LU, Steinbach E, Nossek JA (2009) Models and analysis of streaming video transmission over wireless fading channels. Signal Process Image Commun 24:651–665. doi: 10.1016/j.image.2009.04.005Karki R, Seenivasan T, Claypool M, Kinicki R (2010) Performance Analysis of Home Streaming Video Using Orb. In: Proceedings of the 20th International Workshop on Network and Operating Systems Support for Digital Audio and Video. ACM, New York, NY, USA, pp 111–116Ke C-H (2012) myEvalSVC-an Integrated Simulation Framework for Evaluation of H. 264/SVC Transmission. KSII Trans Internet Inf Syst (TIIS) 6:377–392. doi: 10.3837/tiis.2012.01.021Ke C-H, Shieh C-K, Hwang W-S, Ziviani A (2008) An Evaluation Framework for More Realistic Simulations of MPEG Video Transmission. J Inf Sci Eng 24:425–440Klaue J, Rathke B, Wolisz A (2003) Evalvid–A framework for video transmission and quality evaluation. In: Computer Performance Evaluation. Modelling Techniques and Tools. Springer, pp 255–272Le TA, Nguyen H (2014) End-to-end transmission of scalable video contents: performance evaluation over EvalSVC—a new open-source evaluation platform. Multimed Tools Appl 72:1239–1256. doi: 10.1007/s11042-013-1444-6Lie A, Klaue J (2008) Evalvid-RA: trace driven simulation of rate adaptive MPEG-4 VBR video. Multimedia Systems 14:33–50. doi: 10.1007/s00530-007-0110-0Moving Pictures Experts Group and ITU-T Video Coding Experts Group (2011) H. 264/SVC reference software (JSVM 9.19.14) and Manual.Nightingale J, Wang Q, Grecos C (2014) Empirical evaluation of H.264/SVC streaming in resource-constrained multihomed mobile networks. Multimed Tools Appl 70:2011–2035. doi: 10.1007/s11042-012-1219-5Parmar H, Thornburgh M (2012) Real-Time Messaging Protocol (RTMP) Specification. AdobePolitis I, Dounis L, Dagiuklas T (2012) H. 264/SVC vs. H. 264/AVC video quality comparison under QoE-driven seamless handoff. Signal Process Image Commun 27:814–826Pozueco L, Pañeda XG, García R, et al. (2013) Adaptable system based on Scalable Video Coding for high-quality video service. Comput Electr Eng 39:775–789. doi: 10.1016/j.compeleceng.2013.01.015Pozueco L, Pañeda XG, García R, et al. (2014) Adaptation engine for a streaming service based on MPEG-DASH. Multimed Tools Appl 1–20. doi: 10.1007/s11042-014-2034-ySchwarz H, Marpe D, Wiegand T (2007) Overview of the Scalable Video Coding Extension of the H.264/AVC Standard. IEEE Trans Circ Syst Video Technol 17:1103–1120. doi: 10.1109/TCSVT.2007.905532Seo H-Y (2013) An Efficient Transmission Scheme of MPEG2-TS over RTP for a Hybrid DMB System. ETRI J 35:655–665. doi: 10.4218/etrij.13.0112.0124Sohn H, Yoo H, De Neve W, et al. (2010) Full-Reference Video Quality Metric for Fully Scalable and Mobile SVC Content. IEEE Trans Broadcast 56:269–280. doi: 10.1109/TBC.2010.2050628Sousa-Vieira M-E (2011) Suitability of the M/G/∞ process for modeling scalable H.264 video traffic. In: Analytical and Stochastic Modeling Techniques and Applications. Springer, pp 149–158Tanwir S, Perros H (2013) A Survey of VBR Video Traffic Models. IEEE Commun Surv Tutor 15:1778–1802. doi: 10.1109/SURV.2013.010413.00071Tanwir S, Perros HG (2014) VBR Video Traffic Models. Wiley, HobokenThe Network Simulator (NS-2). http://www.isi.edu/nsnam/ns . Accessed 6 Feb 2015Unanue I, Urteaga I, Husemann R, et al. (2011) A Tutorial on H. 264/SVC Scalable Video Coding and its Tradeoff between Quality, Coding Efficiency and Performance. Recent Advances on Video Coding 1–24.Van der Auwera G, David PT, Reisslein M, Karam LJ (2008) Traffic and quality characterization of the H. 264/AVC scalable video coding extension. Adv Multimedia 2008:1Wang Y, Claypool M (2005) RealTracer—Tools for Measuring the Performance of RealVideo on the Internet. Multimed Tools Appl 27:411–430. doi: 10.1007/s11042-005-3757-6Wang Z, Lu L, Bovik AC (2004) Video quality assessment based on structural distortion measurement. Signal Process Image Commun 19:121–132. doi: 10.1016/S0923-5965(03)00076–6Wien M, Schwarz H, Oelbaum T (2007) Performance Analysis of SVC. IEEE Trans Circ Syst for Video Technol 17:1194–1203. doi: 10.1109/TCSVT.2007.905530YUV video repository. ftp://ftp.tnt.uni-hannover.de/pub/svc/testsequences/ . Accessed 10 Jan 201

    Evaluation of the MDC and FEC over the quality of service and quality of experience for video distribution in ad hoc networks

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    Mobile ad hoc networks (MANETs) offer an excellent scenario for deploying communication applications because of the connectivity and versatility of this kind of networks. In contrast, the topology is usually extremely dynamic causing high rate of packet loss, so that ensuring a specific Quality of Service (QoS) for real-time video services becomes a hard challenge. In this paper, we evaluate the effect of using Multiple Description Coding (MDC) and Forward Error Correction (FEC) techniques for improving video quality in a multimedia content distribution system. A hybrid architecture using fixed and wireless ad hoc networks is proposed, which enables the use of multipoint-to-point transmission. MDC and FEC mechanisms can be combined with multipath transmission to increase the network efficiency and recover lost packets, improving the overall Quality of Experience (QoE) of the receiver. Simulations have been analyzed paying attention to objective parameters (Peak Signal to Noise Ratio, Packet Delivery Ratio, Decodable Frame Rate and interruptions) and subjective parameters. Results show that MDC increases the probability of packet delivery and FEC is able to recover lost frames and reduce video interruptions in moderate mobility scenarios, resulting in the improvement of video quality and the final user experience.This work was supported by project MIQUEL (TEC2007- 68119-C02-01/TCM) of the Spanish Ministry of Education and Science. The authors would like to thank the Editor and the reviewers for helpful suggestions to improve the quality of this paper.Acelas Delgado, P.; Arce Vila, P.; Guerri Cebollada, JC.; Castellanos Hernández, WE. (2014). Evaluation of the MDC and FEC over the quality of service and quality of experience for video distribution in ad hoc networks. Multimedia Tools and Applications. 68(3):969-989. https://doi.org/10.1007/s11042-012-1111-3969989683Apostolopoulos JG, Wong T, Tan W, Wee SJ (2002) On multiple description streaming with content delivery networks. IEEE INFOCOMBoukerche A (2009) Algorithms and protocols for wireless and mobile ad hoc networks. John Wiley & Sons IncChow CO, Ishii H (2007) Enhancing real-time video streaming over mobile ad hoc networks using multipoint-to-point communication. Comput Commun 30:1754–1764Clausen T, Jacquet P (2003) Optimized link state routing protocol (OLSR), RFC 3626Corrie B et al (2003) Towards quality of experience in advanced collaborative environments. Third Annual Workshop on Advanced Collaborative EnvironmentsGabrielyan E, Hersch R (2006) Reliable multi-path routing schemes for real-time streaming. International Conference on Digital Telecommunications, pp 65–65Gandikota VR, Tamma BR, Murthy CSR (2008) Adaptive-FEC based packet loss resilience scheme for supporting voice communication over adhoc wireless networks. IEEE Trans Mobile Comput 7:1184–1199Gharavi H (2008) Multi-channel for multihop communication links. International Conference on Telecommunications, pp 1–6Grega M, Janowski L, Leszczuk M, Romaniak P, Papir Z (2008) Quality of experience evaluation for multimedia services. Przegląd Telekomunikacyjny i Wiadomości Telekomunikacyjne 4:142–153Hsieh MY, Huang YM, Chian TC (2007) Transmission of layered video streaming via multi-path on ad hoc networks. Multimed Tool Appl 34:155–177ITU—International Telecommunication Union (2007) Definition of quality of experience (QoE)”, Reference: TD 109rev2 (PLEN/12)ITU-R Recommendation BT.500-12 (2009) Methodology for the subjective assessment of the quality of television pictures. International Telecommunication Union, GenevaITU-T Recommendation P.910 (2000) Subjective video quality assessment methods for multimedia applications. International Telecommunication Union, GenevaKao KL, Ke ChH, Shieh CH (2006) An advanced simulation tool-set for video transmission performance evaluation. IEEE Region 10 Conference, pp 1–40Ke CH et al (2006) A novel realistic simulation tool for video transmission over wireless network. Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trsutworthy ComputingKeisuke U, Cheeonn C, Hiroshi I (2008) A study on video performance of multipoint-to-point video streaming with multiple description coding over ad hoc networks. EEJ Trans Electron, Inf Syst 128:1431–1437Kilkki K (2008) Quality of experience in communications ecosystem. J Univers Comput Sci 14:615–624Li A (2007) RTP payload format for generic forward error correction. RFC 5109, Dec. 2007Li J, Blake C, Couto DD, Lee H, Morris R (2001) Capacity of ad hoc wireless networks. 7th Annual International Conference on Mobile Computing and Networking, pp 16–21Liao Y, Gibson JD (2011) Routing-aware multiple description video coding over mobile ad-hoc networks. IEEE Trans Multimed 13:132–142Lindeberg M, Kristiansen S, Plagemann T, Goebel V (2011) Challenges and techniques for video streaming over mobile ad hoc networks. Multimed Syst 17:51–82Mao S et al (2003) Video transport over ad hoc networks: multistream coding with multipath transport. IEEE J Sel Area Comm 21:1721–1737Ni P (2009) Towards Optimal Quality of Experience Via Scalable Video Coding. Mälardalen University Press Licentiate Theses, SwedenPinson MH, Wolf S (2004) A new standardized method for objectively measuring video quality. IEEE Trans Broadcast 50:312–322Rong B, Qian Y, Lu K, Hu RQ, Kadoch M (2010) Multipath routing over wireless mesh networks for multiple description video transmission. IEEE J Sel Area Comm 28:321–331Schierl T, Ganger K, Hellge C, Wiegand T, Stockhammer T (2006) SVC-based multisource streaming for robust video trans- mission in mobile ad hoc networks. IEEE Wireless Comm 13:96–103Schierl T, Stockhammer T, Wiegand T (2007) Mobile video transmission using scalable video coding. IEEE Trans Circ Syst Video Tech 17:1204–1217Schwarz H, Marpe D, Wiegand T (2007) Overview of the scalable video coding extension of the H.264/AVC standard. IEEE Trans Circ Syst Video Tech 17:1103–1120VQEG (2008) Video quality experts group. Available online: http://www.vqeg.orgWang Z et al (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13:600–612Wei W, Zakhor A (2004) Robust multipath source routing protocol (RMPSR) for video communication over wireless ad hoc net- works. Proceedings of IEEE International Conference on Multimedia and Expo 2:1379–1382Winkler S, Mohandas P (2008) The evolution of video quality measurement: from PSNR to hybrid metrics. IEEE Trans Broadcast 54:660–668Xunqi Y, Modestino JW, Bajic IV (2005) Performance analysis of the efficacy of packet-level FEC in improving video transport over networks. IEEE International Conference on Image Processing 2:177–180Zink M, Schmitt J, Steinmetz R (2005) Layer-encoded video in scalable adaptive streaming. IEEE Trans Multimed 7:75–8

    Hybrid FLUTE/DASH video delivery over mobile wireless networks

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    This paper describes how FLUTE (File Delivery over Unidirectional Transport) and DASH (Dynamic Adaptive Streaming over HTTP) can be used to provide mobile video streaming services over broadcast wireless networks. FLUTE is a multicast protocol for multimedia file download. In this proposal, the protocol is adapted to provide video streaming services in crowded environments. Thus, video is delivered over a single connection to all viewers, reducing the traffic in the network. FLUTE incorporates an AL-FEC (Application Layered Forward Error Correction) mechanism in order to improve the reliability of the broadcast communication channel. For streaming applications, AL-FEC improves the relationship between the PSNR (Peak Signal-to-Noise Ratio) of the received video and the bandwidth allocated to the broadcast connection. The AL-FEC hereby presented applies simple unequal error protection schemes to favor the download of key frames. Furthermore, the proposal is based on the same video segmentation mechanism as DASH and therefore, clients can connect to a DASH repository to repair errors in the segments. This paper shows that FLUTE and DASH can be seamlessly integrated into a hybrid broadcast/unicast streaming technology, providing flexibility to trade off PSNR and bandwidth depending on the conditions of the mobile network.This work was supported by the 11012 ICARE (Innovative Cloud Architecture for Real Entertainment) project within the ITEA 2 Call 6 Program of the European Union.Belda Ortega, R.; De Fez Lava, I.; Fraile Gil, F.; Arce Vila, P.; Guerri Cebollada, JC. (2014). Hybrid FLUTE/DASH video delivery over mobile wireless networks. Transactions on Emerging Telecommunications Technologies. 25(11):1070-1082. doi:10.1002/ett.2804S107010822511ETSI TS 126 346 v11.3.0. Universal Mobile Telecommunications Systems (UMTS); LTE; Multimedia Broadcast/Multicast Service (MBMS); Protocols and Codecs 2013Lecompte, D., & Gabin, F. (2012). Evolved multimedia broadcast/multicast service (eMBMS) in LTE-advanced: overview and Rel-11 enhancements. IEEE Communications Magazine, 50(11), 68-74. doi:10.1109/mcom.2012.6353684Stockhammer T Luby MG DASH in mobile networks and services. Presented at IEEE Visual Communications and Image Processing (VCIP) , 2012Seeling, P., & Reisslein, M. (2012). Video Transport Evaluation With H.264 Video Traces. IEEE Communications Surveys & Tutorials, 14(4), 1142-1165. doi:10.1109/surv.2011.082911.00067Zhao, S., Tuninetti, D., Ansari, R., & Schonfeld, D. (2012). Multiple description coding over multiple correlated erasure channels. Transactions on Emerging Telecommunications Technologies, 23(6), 522-536. doi:10.1002/ett.2507Lin, C.-H., Wang, Y.-C., Shieh, C.-K., & Hwang, W.-S. (2012). An unequal error protection mechanism for video streaming over IEEE 802.11e WLANs. Computer Networks, 56(11), 2590-2599. doi:10.1016/j.comnet.2012.04.004Paila T Walsh R Luby M Roca V Lehtonen R FLUTE - file delivery over unidirectional transport. 2012Luby M Watson M Vicisano L Asynchronous layered coding (ALC) protocol instantiation. 2010Ameigeiras, P., Ramos-Munoz, J. J., Navarro-Ortiz, J., & Lopez-Soler, J. M. (2012). Analysis and modelling of YouTube traffic. Transactions on Emerging Telecommunications Technologies, 23(4), 360-377. doi:10.1002/ett.2546ISO/IEC 23009-1. Dynamic adaptive streaming over HTTP (DASH) - Part 1: media presentation description and segment formats 2012De Fez, I., Fraile, F., Belda, R., & Guerri, J. C. (2012). Analysis and Evaluation of Adaptive LDPC AL-FEC Codes for Content Download Services. IEEE Transactions on Multimedia, 14(3), 641-650. doi:10.1109/tmm.2012.2190392Jenkac, H., Stockhammer, T., & Wen Xu. (2006). Asynchronous and reliable on-demand media broadcast. IEEE Network, 20(2), 14-20. doi:10.1109/mnet.2006.1607891Neumann C Roca V Scalable video streaming over ALC (SVSoA): a solution for the large scale multicast distribution of videos. Presented at 1st Int. Workshop on SMDI , 2004Lederer S Müller C Timmerer C Dynamic adaptive streaming over HTTP dataset Proc. of the ACM Conference on Multimedia Systems (MMSys) 2012 89 94Blender Foundation webpage http://www.blender.org/blenderorg/Bai, H., & Atiquzzaman, M. (2003). Error modeling schemes for fading channels in wireless communications: A survey. IEEE Communications Surveys & Tutorials, 5(2), 2-9. doi:10.1109/comst.2003.5341334Ohm, J.-R. (2004). Multimedia Communication Technology. Signals and Communication Technology. doi:10.1007/978-3-642-18750-

    Multi path multi priority (MPMP) scalable video streaming for mobile applications

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    On the merits of SVC-based HTTP adaptive streaming

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    HTTP Adaptive Streaming (HAS) is quickly becoming the dominant type of video streaming in Over-The-Top multimedia services. HAS content is temporally segmented and each segment is offered in different video qualities to the client. It enables a video client to dynamically adapt the consumed video quality to match with the capabilities of the network and/or the client's device. As such, the use of HAS allows a service provider to offer video streaming over heterogeneous networks and to heterogeneous devices. Traditionally, the H. 264/AVC video codec is used for encoding the HAS content: for each offered video quality, a separate AVC video file is encoded. Obviously, this leads to a considerable storage redundancy at the video server as each video is available in a multitude of qualities. The recent Scalable Video Codec (SVC) extension of H. 264/AVC allows encoding a video into different quality layers: by dowloading one or more additional layers, the video quality can be improved. While this leads to an immediate reduction of required storage at the video server, the impact of using SVC-based HAS on the network and perceived quality by the user are less obvious. In this article, we characterize the performance of AVC- and SVC-based HAS in terms of perceived video quality, network load and client characteristics, with the goal of identifying advantages and disadvantages of both options

    Random Linear Network Coding for 5G Mobile Video Delivery

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    An exponential increase in mobile video delivery will continue with the demand for higher resolution, multi-view and large-scale multicast video services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a number of new opportunities for optimizing video delivery across both 5G core and radio access networks. One of the promising approaches for video quality adaptation, throughput enhancement and erasure protection is the use of packet-level random linear network coding (RLNC). In this review paper, we discuss the integration of RLNC into the 5G NR standard, building upon the ideas and opportunities identified in 4G LTE. We explicitly identify and discuss in detail novel 5G NR features that provide support for RLNC-based video delivery in 5G, thus pointing out to the promising avenues for future research.Comment: Invited paper for Special Issue "Network and Rateless Coding for Video Streaming" - MDPI Informatio
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