Sustainable OTT video distribution powered by 5G-multicast/unicast delivery and versatile video coding

Video over the internet has drastically grown these past years, currently representing more than 80% of the internet bandwidth [3]. The massive usage of unicast delivery leads to network congestion that can result in poor quality of experience for the viewer, high delivery cost for operators and increased energy consumption. The current methods for adaptive video streaming rely more on maximizing the video quality for a given bandwidth rather than minimizing the end-to-end (from video server to end-user display) energy consumption for a given level of quality. This paper aims at leveraging recently standardized delivery and coding technologies to maintain the video quality while monitoring and reducing video energy footprint and delivery costs.

The Versatile Video Coding (VVC) [2] recently issued by ISO/IEC and ITU-T is used to further reduce video services bandwidth over previous video coding solutions, in particular its predecessor HEVC [10]. Compared to HEVC, VVC enables around 50% of bandwidth saving, at an equivalent video quality [12]. This performance is achieved by extending existing HEVC coding tools and by introducing new ones. VVC also brings new high-level features to better address new use-cases and applications (e.g variable resolution, scalability, 360° and screen-content coding). This paper uses ATEME Titan encoder while the decoding is performed by a real time software decoder OpenVVC. This latter is a cross-platform library that provides consumers with real time decoding capability under different OS including MAC OS, Windows, Linux and Android on Intel x86 and ARM platforms.

A dynamic video format selection is proposed to limit the distribution bandwidth and energy cost based on quality/complexity tradeoffs sent to the player. The carriage of such metadata is achieved by using the Green-MPEG [6] and DASH standard. A content mapping and video artefacts masking is implemented to counterbalance video degradation with post-processing. These are based on SEI messages such as CTI and Grain Synthesis recently standardized in the VSEI specification [5]. An energy reporting solution is proposed in order for the end-viewer to be informed of the energy impact and enabling manual adjustment the energy/quality tradeoff.

The Common Media Application Format (CMAF) is used to deliver the video segments over the network [5]. The carriage of video, audio and green metadata is based on the ISO/IEC Base Media File Format [7] (ISOBMFF). To save network traffic, the video segments can be either sent in unicast for low-audience services or in multicast for highly popular ones. The DASH/FLUTE stack is implemented as multicast protocol. The OTT services are delivered in the context of 3GPP Release 17 [1] and DVB-MABR Phase 2 network [4], including delivery over managed networks (IPTV) and mobile (4G-Lte and 5G).

The estimated energy saving for the proposed delivery infrastructure is the following. First, the bitrate saving brought by improved compression is estimated to be .05-0.1 Wh/bit for 1 bit of transmitted video [11], representing 37.5-75kWh saving for a 5Mbps HEVC HD service. Usage of SL-HDR is estimated to save 15-20% of display energy [9], and even more for a receiver fully leveraging Green metadata. For an average TV set [8], it represents a 21kWh saving. Finally, radio saving is more complex to estimate, but preliminary results show that saving from multicast starts from 1-8 User-Equipment (UE) in a cell.

This paper proposes an OTT delivery solution enabling operators and end-users to monitor and control their energy impact. At the headend side, metadata are generated by a pre-processing block and embedded in SEI messages. The encoder is leveraging VVC and CMAF to encapsulate video services together with the metadata. The delivery network is optimized by using DASH/FLUTE profile of DVB-MABR to save bandwidth when OTT content are delivered over IPTV or mobile networks. On end-user side, a real-time software VVC decoding and post-decoding processing are demonstrated. An end-to-end demonstrator is provided and evaluated to assess the relevance of the proposed method in a real environment.