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ALPHAS: Adaptive Bitrate Ladder Optimization for Multi-Live Video Streaming

dc.contributor.authorTashtarian, Farzad
dc.contributor.authorDolati, Mahdi
dc.contributor.authorLorenzi, Daniele
dc.contributor.authorMozhganfar, Mojtaba
dc.contributor.authorGorinsky, Sergey 
dc.contributor.authorKhonsari, Ahmad
dc.contributor.authorTimmerer, Christian
dc.contributor.authorHellwagner, Hermann
dc.date.accessioned2025-01-13T16:22:17Z
dc.date.available2025-01-13T16:22:17Z
dc.date.issued2025-05-19
dc.identifier.citation[1] Sandvine, “The Global Internet Phenomena Report,” 2024. [Online]. Available: https://bit.ly/sandvine report [2] Ericsson, “Ericsson Mobility Report,” 2024. [Online]. Available: https://bit.ly/ericsson mobility report [3] Z. Zheng, Y. Ma, Y. Liu, F. Yang, Z. Li, Y. Zhang, J. Zhang, W. Shi, W. Chen, D. Li, Q. An, H. Hong, H. H. Liu, and M. Zhang, “XLINK: QoE-Driven Multi-Path QUIC Transport in Large-Scale Video Services,” in SIGCOMM, 2021, p. 418–432. [4] A. Bentaleb, B. Taani, A. C. Begen, C. Timmerer, and R. Zimmermann, “A Survey on Bitrate Adaptation Schemes for Streaming Media Over HTTP,” IEEE Communications Surveys & Tutorials, vol. 21, no. 1, pp. 562–585, 2019. [5] X. Zuo, J. Yang, M. Wang, and Y. Cui, “Adaptive Bitrate with User- Level QoE Preference for Video Streaming,” in INFOCOM, 2022, pp. 1279–1288. [6] Twitch, “Broadcasting Guidelines.” [Online]. Available: https://help. twitch.tv/s/article/broadcasting-guidelines [7] YouTube, “Choose Live Encoder Settings, Bitrates, and Resolutions.” [Online]. Available: https://support.google.com/youtube/ answer/2853702 [8] THEOlive, “Stream Configuration.” [Online]. Available: https: //developers.theo.live/docs/stream-configuration [9] MUX, “Configure Broadcast Software.” [Online]. Available: https: //docs.mux.com/guides/video/configure-broadcast-software [10] Bitmovin, “Dashboard, Live Encoder.” [Online]. Available: https: //bitmovin.com/dashboard/live [11] A. Aaron, Z. Li, M. Manohara, J. De Cock, and D. Ronca, “Per-Title Encode Optimization,” Netflix Technology Blog, 2015. [Online]. Available: https://netflixtechblog.com/per-title-encode-optimization-7e99442b62a2 [12] I. Katsavounidis, “Dynamic Optimizer — A Perceptual Video Encoding Optimization Framework,” Netflix Technology Blog, 2018. [Online]. Available: https://bit.ly/dynamic optimizer [13] J. De Cock, Z. Li, M. Manohara, and A. Aaron, “Complexity-Based Consistent-Quality Encoding in the Cloud,” in ICIP, 2016, pp. 1484– 1488. [14] V. V. Menon, H. Amirpour, M. Ghanbari, and C. Timmerer, “Perceptually-Aware Per-Title Encoding for Adaptive Video Streaming,” in ICME, 2022, pp. 1–6. [15] V. V. Menon, P. T. Rajendran, C. Feldmann, K. Schoeffmann, M. Ghanbari, and C. Timmerer, “JND-Aware Two-Pass Per-Title Encoding Scheme for Adaptive Live Streaming,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 34, no. 2, pp. 1281–1294, 2024. [16] H. Amirpour, R. Schatz, and C. Timmerer, “Between Two and Six? Towards Correct Estimation of JND Step Sizes for VMAF-Based Bitrate Laddering,” in QoMEX, 2022, pp. 1–4. [17] T. Huang, R.-X. Zhang, and L. Sun, “Deep Reinforced Bitrate Ladders for Adaptive Video Streaming,” in NOSSDAV, 2021, p. 66–73. [18] P. Lebreton and K. Yamagishi, “Network and Content-Dependent Bitrate Ladder Estimation for Adaptive Bitrate Video Streaming,” in ICASSP, 2021, pp. 4205–4209. [19] ——, “Quitting Ratio-Based Bitrate Ladder Selection Mechanism for Adaptive Bitrate Video Streaming,” IEEE Transactions on Multimedia, vol. 25, pp. 8418–8431, 2023. [20] F. Tashtarian, A. Bentaleb, H. Amirpour, B. Taraghi, C. Timmerer, H. Hellwagner, and R. Zimmermann, “LALISA: Adaptive Bitrate Ladder Optimization in HTTP-Based Adaptive Live Streaming,” in NOMS, 2023, pp. 1–9. [21] M. Seufert, M. Spangenberger, F. Poign´ee, F. Wamser, W. Robitza, C. Timmerer, and T. Hossfeld, “COBIRAS: Offering A Continuous Bit Rate Slide to Maximize DASH Streaming Bandwidth Utilization,” ACM Transactions on Multimedia Computing, Communications, and Applications, 2024. [22] J. Dilley, B. M. Maggs, J. Parikh, H. Prokop, R. K. Sitaraman, and B. Weihl, “Globally Distributed Content Delivery,” IEEE Internet Computing, vol. 6, no. 5, pp. 50–58, 2002. [23] A. Bentaleb, M. Lim, M. N. Akcay, A. C. Begen, and R. Zimmermann, “Common Media Client Data (CMCD): Initial Findings,” in NOSSDAV, 2021, p. 25–33. [24] F. Tashtarian, A. Bentaleb, H. Amirpour, S. Gorinsky, J. Jiang, H. Hellwagner, and C. Timmerer, “ARTEMIS: Adaptive Bitrate Ladder Optimization for Live Video Streaming,” in NSDI, 2024, pp. 591–611. [25] S. Hasan, S. Gorinsky, C. Dovrolis, and R. K. Sitaraman, “Trade-Offs in Optimizing the Cache Deployments of CDNs,” in INFOCOM, 2014, pp. 460–468. [26] H. Amirpour, J. Zhu, P. Le Callet, and C. Timmerer, “A Real-Time Video Quality Metric for HTTP Adaptive Streaming,” in ICASSP, 2024, pp. 3810–3814. [27] Z. Li, C. Bampis, J. Novak, A. Aaron, K. Swanson, A. Moorthy, and J. De Cock, “VMAF: The Journey Continues,” Netflix Technology Blog, 2018. [Online]. Available: https://bit.ly/4d6SrRE [28] Blender, “Big Buck Bunny.” [Online]. Available: https://bit.ly/3YqoaZu [29] FFmpeg, “FFmpeg.” [Online]. Available: https://www.ffmpeg.org [30] J. Jiang, V. Sekar, and H. Zhang, “Improving Fairness, Efficiency, and Stability in HTTP-Based Adaptive Video Streaming with FESTIVE,” in CoNEXT, 2012, p. 97–108. [31] T. X. Tran and D. Pompili, “Adaptive Bitrate Video Caching and Processing in Mobile-Edge Computing Networks,” IEEE Transactions on Mobile Computing, vol. 18, no. 9, pp. 1965–1978, 2019. [32] Y. Azar and I. Gamzu, “Efficient Submodular Function Maximization under Linear Packing Constraints,” in ICALP, 2012, pp. 38–50. [33] DASH Industry Forum, “Client Implementation for the Playback of MPEG-DASH via Javascript.” [Online]. Available: https://github.com/ Dash-Industry-Forum/dash.js [34] Gurobi Optimization, “Gurobi Optimizer.” [Online]. Available: https: //www.gurobi.com/solutions/gurobi-optimizer [35] T. Huang, C. Zhou, R.-X. Zhang, C. Wu, X. Yao, and L. Sun, “Comyco: Quality-Aware Adaptive Video Streaming via Imitation Learning,” in MM, 2019, p. 429–437. [36] D. Yuan, T. Zhao, Y. Xu, H. Xue, and L. Lin, “Visual JND: A Perceptual Measurement in Video Coding,” IEEE Access, vol. 7, pp. 29 014–29 022, 2019. [37] M. Seufert, S. Egger, M. Slanina, T. Zinner, T. Hoßfeld, and P. Tran- Gia, “A Survey on Quality of Experience of HTTP Adaptive Streaming,” IEEE Communications Surveys & Tutorials, vol. 17, no. 1, pp. 469–492, 2015. [38] Apple, “HTTP Live Streaming (HLS) Authoring Specification for Apple Devices,” 2015. [Online]. Available: https://bit.ly/apple hls [39] ISO/IEC. 2022, “Information Technology — Dynamic Adaptive Streaming over HTTP (DASH) — Part 1: Media Presentation Description and Segment Formats,” International Organization for Standardization, International Standard 23009-1:2022, 2022. [40] A. V. Katsenou, F. Zhang, K. Swanson, M. Afonso, J. Sole, and D. R. Bull, “VMAF-Based Bitrate Ladder Estimation for Adaptive Streaming,” in PCS, 2021, pp. 1–5. [41] C. Chen, Y.-C. Lin, S. Benting, and A. Kokaram, “Optimized Transcoding for Large Scale Adaptive Streaming Using Playback Statistics,” in ICIP, 2018, pp. 3269–3273. [42] A. Premkumar, P. T. Rajendran, V. V. Menon, A. Wieckowski, B. Bross, and D. Marpe, “Quality-Aware Dynamic Resolution Adaptation Framework for Adaptive Video Streaming,” in MMSys, 2024, p. 292–298. [43] H. Amirpour, C. Timmerer, and M. Ghanbari, “PSTR: Per-Title Encoding Using Spatio-Temporal Resolutions,” in ICME, 2021, pp. 1–6. [44] M. Bhat, J.-M. Thiesse, and P. L. Callet, “Combining Video Quality Metrics to Select Perceptually Accurate Resolution in A Wide Quality Range: A Case Study,” in ICIP, 2021, pp. 2164–2168. [45] Y. A. Reznik, K. O. Lillevold, A. Jagannath, J. Greer, and J. Corley, “Optimal Design of Encoding Profiles for ABR Streaming,” in PV, 2018, p. 43–47. [46] L. Toni, R. Aparicio-Pardo, K. Pires, G. Simon, A. Blanc, and P. Frossard, “Optimal Selection of Adaptive Streaming Representations,” ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 11, no. 2s, 2015. [47] L. Peroni, S. Gorinsky, and F. Tashtarian, “In-Band Quality Notification from Users to ISPs,” in CloudNet, 2024, pp. 332–338. [48] D. K. Krishnappa, M. Zink, and R. K. Sitaraman, “Optimizing the Video Transcoding Workflow in Content Delivery Networks,” in MMSys, 2015, pp. 37–48. [49] A. Erfanian, H. Amirpour, F. Tashtarian, C. Timmerer, and H. Hellwagner, “LwTE: Light-Weight Transcoding at the Edge,” IEEE Access, vol. 9, pp. 112 276–112 289, 2021.es
dc.identifier.urihttps://hdl.handle.net/20.500.12761/1891
dc.description.abstractLive streaming routinely relies on the Hypertext Transfer Protocol (HTTP) and content delivery networks (CDNs) to scalably disseminate videos to diverse clients. A bitrate ladder refers to a list of bitrate-resolution pairs, or representations, used for encoding a video. A promising trend in HTTP-based video streaming is to adapt not only the client's representation choice but also the bitrate ladder during the streaming session. This paper examines the problem of multi-live streaming, where an encoding service coordinates CDN-assisted bitrate ladder adaptation for multiple live streams delivered to heterogeneous clients in different zones via CDN edge servers. We design ALPHAS, a practical and scalable system for multi-live streaming that accounts for CDNs' bandwidth constraints and encoders' computational capabilities and also supports stream prioritization. ALPHAS, aware of both video content and streaming context, seamlessly integrates with the end-to-end streaming pipeline and operates in real time transparently to clients and encoding algorithms. We develop a cloud-based ALPHAS implementation and evaluate it through extensive real-world and trace-driven experiments against four prominent baseline approaches that encode each stream independently. The evaluation shows that ALPHAS outperforms the baselines, improving quality of experience, end-to-end latency, and per-stream processing by up to 23%, 21%, and 49%, respectively.es
dc.description.sponsorshipMICIU/AEI/10.13039/501100011033 and ERDF, EUes
dc.description.sponsorshipAustrian Federal Ministry for Digital and Economic Affairses
dc.description.sponsorshipNational Foundation for Research, Technology and Development, Austriaes
dc.description.sponsorshipChristian Doppler Research Associationes
dc.language.isoenges
dc.titleALPHAS: Adaptive Bitrate Ladder Optimization for Multi-Live Video Streaminges
dc.typeconference objectes
dc.conference.date19–22 May 2025es
dc.conference.placeLondon, United Kingdomes
dc.conference.titleIEEE International Conference on Computer Communications *
dc.event.typeconferencees
dc.pres.typepaperes
dc.type.hasVersionVoRes
dc.rights.accessRightsopen accesses
dc.acronymINFOCOM*
dc.rankA**
dc.relation.projectIDPID2022-140560OB-I00es
dc.relation.projectNameDRONAC (Distributed Reliable Objects for Networked Applications Coordination)es
dc.relation.projectNameATHENA (AdapTive Streaming over HTTP and Emerging Networked MultimediA Services)es
dc.description.refereedTRUEes
dc.description.statuspubes


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