The Codec Adoption Challenge
Every few years, mathematicians and engineers come out with a new codec that claims to improve the efficiency and quality of video (and audio) streaming. Adoption of these codecs faces a number of obstacles. Some are business-related like encoding or decoding royalties. But on the technology side, new codecs face the chicken vs. egg conundrum: are there enough users with technology capable of using the new codec effectively to justify a switch? Or will device OEMs not install the tech until streaming networks offer the new codec?
With the right kind of device analytics, video OTT networks can answer these questions and build a roadmap that times the switch to new codecs and builds a network architecture that serves devices capable of using the codecs.
There are a handful of new codecs that video technology architects have deployed or are evaluating. These include HEVC, AV1, and (coming soon) VVC. All promise:
- Higher Quality, Lower GB Delivery,
- Lower Delivery Cost, and
- Increased, Longer Audience Engagement
The last benefit of longer audience engagement is particularly sensitive to mobile devices where subscribers have a fixed GB plan with their mobile carrier. When a cricket match goes long, the subscriber’s monthly GB bucket is emptying faster with older, less efficient codecs. Implementation of new, higher efficiency codec could keep that user happy and cheering until the end of the match.
Better Analytics of Your Audience’s Devices
Video OTT subscribers use a wide array of devices, including desktops, smart TVs, smartphones, tablets, streaming devices, and even game consoles. How many of these are ready to effectively use an advanced codec like HEVC?
A device detection solution can answer these questions by monitoring your audience’s device requests. HEVC readiness is defined by a number of factors about the device. For example, a smartphone’s graphical processor unit (GPU), the display resolution, frame refresh rate, and RAM all have some impact on HEVC readiness. In a study monitoring over 12 billion device requests, we monitored the adoption of GPU hardware-supported decoding of the HEVC codec. In 2018, smartphone OEMs had implemented GPUs with HEVC decode support in 57% of Android devices in current use. By 2022, this HEVC support had increased to 91%. Apple iPhones went from 78% in 2018 to 84% in 2022.
In addition to this general GPU-supported HEVC decode capability, a device detection solution can also drill into the more technical question of HEVC level support (https://docs.scientiamobile.com/guides/vcodec-capabilities-inference-values). These levels help define the resolution and frame rate supported. For example, an Samsung S22+ provides Level 6.1 support (8,192 x 4320 resolution @ 60.0 frames per second)
Looking at these general, real-world statistics, it looks like HEVC has well-established support among smartphones. Of course, video OTT providers should analyze their own subscriber base and reach their own conclusion. Changes in media encoding processes and adoption of new bitrate ladders require planning and timing.
Other codecs besides HEVC also need study. AV1 is starting to gain traction. Smartphones are just now starting to include GPUs that decode AV1. Device detection solutions are tracking these so that Video OTT providers can monitor their audience readiness. In the future, Versatile Video Coding (VVC, or sometimes referred to as H.266) is seen as the successor to HEVC. While its rollout timeline is still evolving, it will definitely require a GPU to support its intensive computations.
For many video OTT providers, content delivery network costs are substantial. If a new codec can cut the GB delivered to a large percentage of users in half, then the cost savings can total in the millions. Likewise, viewers will improve satisfaction with higher resolution, faster refresh rates, and lower mobile data charges. But the transition requires device monitoring, analytics, and study before implementation. A device detection solution capable of providing rich, detailed information about video OTT subscribers devices is a critical first step in new codec adoption.
Krishna Guda has driven the development and sales of innovative mobile, web, and software products for over 20 years. Since the founding of ScientiaMobile in 2011, Krishna has led the company to be a leader in mobile device intelligence solutions in launching products ranging from solutions for web and front-end developers to enterprise-grade solutions in the areas of mobile web, image optimization, and device analytics.
Prior to ScientiaMobile, Krishna served in leadership roles in business development, engineering, and product management at innovative companies such as FusionOne, BridgePort Networks, Openwave, and Oracle. He earned his MBA from Kellogg School of Management, Masters from Johns Hopkins University, and an Engineering degree from India.