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      Netflix, Amazon Prime, and YouTube: Comparative Study of Streaming Infrastructure and Strategy

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      https://www.riss.kr/link?id=A108418962

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      다국어 초록 (Multilingual Abstract)

      Netflix, Amazon Prime, and YouTube are the most popular and fastest-growing streaming services globally. Itis a matter of great interest for the streaming service providers to preview their service infrastructure andstreaming strategy in order to prov...

      Netflix, Amazon Prime, and YouTube are the most popular and fastest-growing streaming services globally. Itis a matter of great interest for the streaming service providers to preview their service infrastructure andstreaming strategy in order to provide new streaming services. Hence, the first part of the paper presents adetailed survey of the Content Distribution Network (CDN) and cloud infrastructure of these service providers.
      To understand the streaming strategy of these service providers, the second part of the paper deduces a commonquality-of-service (QoS) model based on rebuffering time, bitrate, progressive download ratio, and standarddeviation of the On-Off cycle. This model is then used to analyze and compare the streaming behaviors of theseservices. This study concluded that the streaming behaviors of all these services are similar as they all useDynamic Adaptive Streaming over HTTP (DASH) on top of TCP. However, the amount of data that theydownload in the buffering state and steady-state vary, resulting in different progressive download ratios,rebuffering levels, and bitrates. The characteristics of their On-Off cycle are also different resulting in differentQoS. Hence a thorough adaptive bit rate (ABR) analysis is presented in this paper. The streaming behaviors ofthese services are tested on different access network bandwidths, ranging from 75 kbps to 30 Mbps. The surveyresults indicate that Netflix QoS and streaming behavior are significantly consistent followed by Amazon Primeand YouTube. Our approach can be used to compare and contrast the streaming services’ strategies and finetunetheir ABR and flow control mechanisms.

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      참고문헌 (Reference) 논문관계도

      1 Google, "Youtube Player API"

      2 M. H. Mazhar, "Real-time video quality of experience monitoring for HTTPS and QUIC" 1331-1339, 2018

      3 International Telecommunication Union, "Quality of service regulation manual"

      4 N. Barman, "QoE modeling for HTTP adaptive video streaming : a survey and open challenges" 7 : 30831-30859, 2019

      5 Netflix, "Netflix Open Connect Appliance Deployment Guide"

      6 Streaming Media Alliance, "Key Network Delivery Metrics"

      7 International Telecommunication Union, "ITU-T Recommendation P.800.1: Mean opinion score (MOS)terminology"

      8 International Telecommunication Union, "ITU-T Recommendation P.1203.1: Models and tools for quality assessment of streaming media"

      9 N. Seitz, "ITU-T QoS standards for IP-based networks" 41 (41): 82-89, 2003

      10 "ISO/IEC 23009-1:2014, Information technology - Dynamic adaptive streaming over HTTP (DASH) - Part 1:Media presentation description and segment formats"

      1 Google, "Youtube Player API"

      2 M. H. Mazhar, "Real-time video quality of experience monitoring for HTTPS and QUIC" 1331-1339, 2018

      3 International Telecommunication Union, "Quality of service regulation manual"

      4 N. Barman, "QoE modeling for HTTP adaptive video streaming : a survey and open challenges" 7 : 30831-30859, 2019

      5 Netflix, "Netflix Open Connect Appliance Deployment Guide"

      6 Streaming Media Alliance, "Key Network Delivery Metrics"

      7 International Telecommunication Union, "ITU-T Recommendation P.800.1: Mean opinion score (MOS)terminology"

      8 International Telecommunication Union, "ITU-T Recommendation P.1203.1: Models and tools for quality assessment of streaming media"

      9 N. Seitz, "ITU-T QoS standards for IP-based networks" 41 (41): 82-89, 2003

      10 "ISO/IEC 23009-1:2014, Information technology - Dynamic adaptive streaming over HTTP (DASH) - Part 1:Media presentation description and segment formats"

      11 M. J. Khokhar, "From network traffic measurements to QoE for Internet video" 1-9, 2019

      12 C. Wang, "Comparing cloud content delivery networks for adaptive video streaming" 686-693, 2018

      13 D. Pal, "A survey of standardized approaches towards the quality of experience evaluation for video services: an ITU perspective" 2018 : 1391724-, 2018

      14 J. Kua, "A survey of rate adaptation techniques for dynamic adaptive streaming over HTTP" 19 (19): 1842-1866, 2017

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