Bitrate and Adaptive Streaming: What are We Measuring and Why? ABSTRACT Currently, a significant increase in bandwidth requirements is expected in the next couple of years, particularly due to an increase in the device resolution [1]: a typical bit-rate for the 4K video is between 15 to 18 Mbps, while it is considered to be more than twice the High-Definition (HD) video bit-rate and a factor of nine the Standard-Definition (SD) video bit-rate. As a result, there is currently a strong demand to decrease video transmission bit-rate, substantially without reducing the visual presentation quality [1]. Bitrate is one of the most well-known and intuitively understood concepts in video transmission. With that said, there are several different definitions of how bitrate is measured, and different methods of measurement are applicable for different situations. Video compression standards, such as H.265/MPEG-HEVC [2], provide a normative definition of bitrate which applies to all Network Abstraction Layer (NAL) units or their subset, and it is followed by video encoders in a corresponding manner. However, we are not transmitting “bare” NAL units, and not necessarily doing so in a significantly constrained pipe. In addition, a ubiquitously used definition of bitrate in the MPEG- 2 TS is provided within the measurement technical report for Digital Video Broadcasting (DVB) systems - ETSI 101 290 [3]. Furthermore, the situation is different in the adaptive video streaming: for example, a 1-sec sliding window over a stream is less relevant when the unit of transmission is a segment. MPEG DASH [4] and Apple HLS [5] have their own definitions of bitrate, based on maxima of segment bitrates, and extended signaling for content-adaptive encoding. The concept of a constant-rate “pipe” is also often irrelevant – video traffic is de-facto multiplexed with all other traffic within: e.g., an LTE cell or a service group in a DOCSIS broadband network and CDN storage, and egress become the limiting per-stream factor. With that said, segment-level measurement is important for streaming clients reasoning the sustainability of a given variant. Lastly, ISPs and CDNs often use the so-called Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org. MHV '23, May 7–10, 2023, Denver, CO, USA © 2023 Copyright is held by the owner/author(s). Publication rights licensed to ACM. ACM 979-8-4007-0160-3/23/05…$15.00 https://doi.org/10.1145/3588444.3591042 95/5 burstable model, where 95 th percentile of a 5-min average is used in lieu of second or segment-based calculation. In this work, we first review various bitrate measurement models and illustrate the difference between them by using different measurement methods, which are applied to a set of constant-rate and content-adaptive streams, being generated by a variety of commercial encoders. Then, we show benefits from using the segment rate, rather than a sliding window, as the target rate. The latter approach showed statistically significant improvements in compression efficiency by using the open source x265 encoder [6],[7], which is a popular open-source encoder that generates bitstreams compliant with the HEVC video coding standard [2]. CCS CONCEPTS • Information systems → Information systems applications → Multimedia information systems → Multimedia streaming KEYWORDS bitrate, video streaming, x265, HEVC, H.265, open-source, coding gain, computational complexity. ACM Reference format: Alex Giladi, Dan Grois, Kirithika Kalirathnam, Robert Dandrea, 2023. Bitrate and Adaptive Streaming: What are We Measuring and Why? In Proceedings of ACM MHV conference (MHV’23). ACM, Denver, CO, USA, 1 page. REFERENCES [1] D. Grois et al., "Performance Comparison of Emerging EVC and VVC Video Coding Standards with HEVC and AV1," in SMPTE Motion Imaging Journal, vol. 130, no. 4, pp. 1-12, May 2021. [2] ITU-T, Recommendation H.265 (04/13), Series H: Audiovisual and Multimedia Systems, Infrastructure of audiovisual services – Coding of Moving Video, High Efficiency Video Coding. [3] Technical Report, Measurement guidelines for Digital Video Broadcasting (DVB) systems, Online: https://www.etsi.org/deliver/etsi_tr/101200_101299/101290/01 .02.01_60/tr_101290v010201p.pdf [4] Information technology, Dynamic adaptive streaming over HTTP (DASH) - Part 1: Media presentation description and segment formats, ISO/IEC 23009-1:2012, 2012. [5] Apple HTTP Live Streaming, Online: https://developer.apple.com/documentation/http_live_streaming/ understanding_the_http_live_streaming_architecture [6] Projects from VideoLAN, x265 software library and application, Online: https://www.videolan.org/developers/x265.html. [7] x265 Documentation, Online : https://x265.readthedocs.io/en/stable/index.html Alex Giladi Comcast Denver, USA alex_giladi@comcast.com Dan Grois Comcast Beer-Sheva, Israel dan_grois@comcast.com Kirithika Kalirathnam Multicoreware, Inc Chennai, India kirithika@multicorewareinc.com Robert Dandrea, Comcast Denver, USA robert_dandrea@cable.comcast.com 148