Interference-aware multipath video streaming in vehicular environments

The multipath transmission is one of the suitable transmission methods for high data rate oriented communication such as video streaming. Each video packets are split into smaller frames for parallel transmission via different paths. One path may interfere with another path due to these parallel transmissions. The multipath oriented interference is due to the route coupling which is one of the major challenges in vehicular traffic environments. The route coupling increases channel contention resulting in video packet collision. In this context, this paper proposes an Interference-aware Multipath Video Streaming (I-MVS) framework focusing on link and node disjoint optimal paths. Specifically, a multipath vehicular network model is derived. The model is utilized to develop interference-aware video streaming method considering angular driving statistics of vehicles. The quality of video streaming links is measured based on packet error rate considering non-circular transmission range oriented shadowing effects. Algorithms are developed as a complete operational I-MVS framework. The comparative performance evaluation attests the benefit of the proposed framework considering various video streaming related metrics

SHStream: Self-Healing Framework for HTTP Video-Streaming

HTTP video-streaming is leading delivery of video content over the Internet. This phenomenon is explained by the ubiquity of web browsers, the permeability of HTTP traffic and the recent video technologies around HTML5. However, the inclusion of multimedia requests imposes new requirements on web servers due to responses with lifespans that can reach dozens of minutes and timing requirements for data fragments transmitted during the response period. Consequently, web- servers require real-time performance control to avoid playback outages caused by overloading and performance anomalies. We present SHStream , a self-healing framework for web servers delivering video-streaming content that provides (1) load admit- tance to avoid server overloading; (2) prediction of performance anomalies using online data stream learning algorithms; (3) continuous evaluation and selection of the best algorithm for prediction; and (4) proactive recovery by migrating the server to other hosts using container-based virtualization techniques. Evaluation of our framework using several variants of Hoeffding trees and ensemble algorithms showed that with a small number of learning instances, it is possible to achieve approximately 98% of recall and 99% of precision for failure predictions. Additionally, proactive failover can be performed in less than 1 secon

Performance Evaluation of Scalable Video Streaming in Mobile Ad hoc Networks

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.The development of video streaming services on wireless ad hoc networks is a challenge task as a consequence of different limitations such as bandwidth-constrained, variable capacity links and energy-constrained operation. Moreover, the dynamic topology of nodes causes frequent link failures and high error rates. We propose in this paper a performance evaluation of the scalable video streaming over mobile ad hoc networks. In particular, we focus on the rate-adaptive strategy for streaming scalable video (H.264/SVC). In order to provide QoS mechanisms in the routing process, a new routing protocol is introduced. This protocol estimates the available bandwidth value, which is sent to video source in order to adapt the bit rate during the video transmission. We also propose a simulation framework that supports evaluation studies for scalable video streaming. In the simulation experiments, SVC streams with combined scalability (quality and temporal scalability) were used. As quality scalability method, we used Medium Grain Scalability (MGS). The results reveal that the rate-adaptive method helps avoid or reduce the congestion in MANETs obtaining a better quality in the received videos.Castellanos, W.; Guerri Cebollada, JC.; Arce Vila, P. (2016). Performance Evaluation of Scalable Video Streaming in Mobile Ad hoc Networks. IEEE Latin America Transactions. 14(1):122-129. http://hdl.handle.net/10251/83347S12212914

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

[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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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. 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Proxy Support for HTTP Adaptive Streaming

Not long ago streaming video over the Internet included only short clips of low quality video. Now the possibilities seem endless as professional productions are made available in high definition. This explosion of growth is the result of several factors, such as increasing network performance, advancements in video encoding technology, improvements to video streaming techniques, and a growing number of devices capable of handling video. However, despite the improvements to Internet video streaming this paradigm is still evolving. HTTP adaptive streaming involves encoding a video at multiple quality levels then dividing those quality levels into small chunks. The player can then determine which quality level to retrieve the next chunk from in order to optimize video playback when considering the underlying network conditions. This thesis first presents an experimental framework that allows for adaptive streaming players to be analyzed and evaluated. Evaluation is beneficial because there are several concerns with the adaptive video streaming ecosystem such as achieving a high video playback quality while also ensuring stable playback quality. The primary contribution of this thesis is the evaluation of prefetching by a proxy server as a means to improve streaming performance. This work considers an implementation of a proxy server that is functional with the extremely popular Netflix streaming service, and it is evaluated using two Netflix players. The results show its potential to improve video streaming performance in several scenarios. It effectively increases the buffer capacity of the player as chunks can be prefetched in advance of the player's request then stored on the proxy to be quickly delivered once requested. This allows for degradation in network conditions to be hidden from the player while the proxy serves prefetched data, preventing a reduction to the video quality as a result of an overreaction by the player. Further, the proxy can reduce the impact of the bottleneck in the network, achieving higher throughput by utilizing parallel connections to the server

Simulation and experimental testbed for adaptive video streaming in ad hoc networks

[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

Towards a scalable video interactivity solution over the IMS

Includes bibliographical references (leaves 72-76).Rapid increase in bandwidth and the interactive and scalability features of the Internet provide a precedent for a converged platform that will support interactive television. Next Generation Network platforms such as the IP Multimedia Subsystem (IMS) support Quality of Service (QoS), fair charging and possible integration with other services for the deployment of IPTV services. IMS architecture supports the use of the Session Initiation Protocol (SIP) for session control and the Real Time Streaming Protocol (RTSP) for media control. This study aims to investigate video interactivity designs over the Internet using an evaluation framework to examine the performance of both SIP and RTSP protocols over the IMS over different access networks. It proposes a Three Layered Video Interactivity Framework (TLVIF) to reduce the video processing load on a server

A common analysis framework for simulated streaming-video networks

Distributed media streaming has been driven by the combination of improved media compression techniques and an increase in the availability of bandwidth. This increase has lead to the development of various streaming distribution engines (systems/services), which currently provide the majority of the streaming media available throughout the Internet. This study aimed to analyse a range of existing commercial and open-source streaming media distribution engines, and classify them in such a way as to define a Common Analysis Framework for Simulated Streaming-Video Networks (CAFSS-Net). This common framework was used as the basis for a simulation tool intended to aid in the development and deployment of streaming media networks and predict the performance impacts of both network configuration changes, video features (scene complexity, resolution) and general scaling. CAFSS-Net consists of six components: the server, the client(s), the network simulator, the video publishing tools, the videos and the evaluation tool-set. Test scenarios are presented consisting of different network configurations, scales and external traffic specifications. From these test scenarios, results were obtained to determine interesting observations attained and to provide an overview of the different test specications for this study. From these results, an analysis of the system was performed, yielding relationships between the videos, the different bandwidths, the different measurement tools and the different components of CAFSS-Net. Based on the analysis of the results, the implications for CAFSS-Net highlighted different achievements and proposals for future work for the different components. CAFSS-Net was able to successfully integrate all of its components to evaluate the different streaming scenarios. The streaming server, client and video components accomplished their objectives. It is noted that although the video publishing tool was able to provide the necessary compression/decompression services, proposals for the implementation of alternative compression/decompression schemes could serve as a suitable extension. The network simulator and evaluation tool-set components were also successful, but future tests (particularly in low bandwidth scenarios) are suggested in order to further improve the accuracy of the framework as a whole. CAFSS-Net is especially successful with analysing high bandwidth connections with the results being similar to those of the physical network tests