as well hundreds of thousands of encoding instances
launched in a cloud-based encoding solution.
Finally, as we’ve discussed earlier, one needs to determine whether a particular CAE solution is suitable
for a single application or multiple applications. The
use of the term “application” here means both key
market verticals (e.g., enterprise, media and entertainment, corporate communications) and also mobile operating system apps such as those found on the
Google Play store or Apple’s App Store.
Some CAE solutions may be hard-coded with limited options for content and formats, as a way to optimize the pre-encoding analysis that must take place in
spatial (intraframe) or temporal (interframe) analysis.
Once the main market vertical for a particular CAE
solution is determined and tested, don’t forget to test
for versatility: is the solution versatile enough to handle content encoding parameters for lower-end SD,
720p and 1080p HD, and even up to 4K Ultra HD (UHD)?
As opposed to content-aware encoding, context-
aware encoding takes into account both the type of
content (e.g., action, sports, screen capture) and the
intended playback device, with some context-aware
solutions also refining encoding parameters on an
OVP- or CDN- specific basis.
Context-aware encoding solutions can be purpose-built for a particular content context, or they can start
with a baseline that is then tweaked in a highly customizable, scalable, and tunable way to allow more
flexibility across bitrate ladder rungs that consist of
an intersection of format, resolution, and data rate.
We’re still in the early days of content- and context-aware encoding offerings, with more solutions set to
launch in Q1 and Q2 of 2018. The team at Streaming
Media magazine will keep our eyes peeled for CAE
solutions that offer unique approaches coupled with
consistent bandwidth savings.
Tim Siglin is a streaming industry veteran and longtime contributing
editor to Streaming Media magazine.
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