QBR works with H.264 and H.265, and in HLS,
DASH, Smooth Streaming, and HDS ABR formats. All software modules are free, and you
pay based on two models, either total hours
consumed or number of subscribers.
One Major Short-Term Caution
On its website, MediaMelon claims, “QBR upgrades existing streaming workflows and systems. It uses the encoders, players and asset
libraries you already have, simply adding new
metadata that allows packagers and players to
optimize adaptive bitrate streaming.” While this
may be true in some cases, it’s definitely not true
in all cases, at least in the short term. Here’s why.
As currently implemented (and tested), QBR
can only choose between streams encoded at
the same resolution. Looking at Figure 2, for
example, QBR would only work if all streams
shared the same resolution. If the streams were
360p, 720p, and 1080p, the technology wouldn’t
work. According to company officials, cross-resolution switching is in beta testing, and should
be available soon, perhaps by the time this article is released. While that’s good news, since
many encoding ladders don’t have many repeated resolutions, it also adds to the technical
challenge undertaken by the server-side module that creates the complexity map that controls the operation.
Specifically, today, the nonreferential content analyzer only has to compare streams of
the same resolution, assessing, for example,
how much better a 6Mbps 1080p streams looks
than a 4.5Mbps 1080p stream. Once MediaMelon
releases cross-resolution operation, it will have
to compare 360p 1.2Mbps with 540p 1.8Mbps,
balancing the quality loss inherent to scaling to
lower resolutions with the greater compression
loss of the lower bits-per-pixel values of higher-resolution videos.
As an example, Netflix solves this riddle by
encoding at multiple resolutions and quality
levels and comparing the results with Video Mul-
timethod Assessment Fusion (VMAF), a time-
consuming, brute-force approach that’s war-
ranted by the amount of video views each Net-
flix video normally achieves. You Tube uses a
neural network, and other vendors, like Bright-
cove and Capella Systems, encode the content
one or more times to gauge complexity. All use
referential quality control metrics that compare
the encoded file with the original, a luxury that
MediaMelon doesn’t have.
How well MediaMelon can manage this transition, and whether its tools can still perform it
for live video, remains to be seen. Still, analyzing what’s in front of us today, MediaMelon delivered on most promises, though your results
will vary by content type, encoding ladder, and
average viewer bandwidth.
We focused our tests on two issues: Does QBR
save bandwidth? And can it save up bits during
simple regions to enable higher bitrate delivery
for complex regions?
To make our encoded media receptive to
QBR operation, we created an encoding ladder with three instances of 360p resolution, at
500Kbps, 900Kbps, and 1300Kbps; two at 720p,
at 1.8Mbps and 2.6Mbps; and three at 1080p, at
4.3Mbps, 5.7Mbps, and 8.1Mbps. Originally, we
encoded our test clips ourselves and sent them
to MediaMelon, but after several corrections,
we sent the original media files to MediaMelon
for their preparation. We played back all videos
from a test page created by MediaMelon that
used the hls.js player.
We tested at multiple bandwidths by using
a hardware throttling tool and recording segments downloaded with the Charles Web Debugging Proxy app. Not surprisingly, our results
varied significantly by effective throughput. Two
issues that impacted the throughput levels that
we tested are illustrated in Netflix’s ISP Speed
Index and Akamai’s State of the Internet report,
which paint very different pictures.
According to Netflix, “The Netflix ISP Speed
Index is a measure of prime time Netflix performance on particular ISPs (internet service
providers) around the globe, and not a measure of overall performance for other services/
data that may travel across the specific ISP