  The integration of advanced video codecs into the streaming pipeline is
growing in response to the increasing demand for high quality video content.
However, the significant computational demand for advanced codecs like
Versatile Video Coding (VVC) poses challenges for service providers, including
longer encoding time and higher encoding cost. This challenge becomes even more
pronounced in streaming, as the same content needs to be encoded at multiple
bitrates (also known as representations) to accommodate different network
conditions. To accelerate the encoding process of multiple representations of
the same content in VVC, we employ the encoding map of a single representation,
known as the reference representation, and utilize its partitioning structure
to accelerate the encoding of the remaining representations, referred to as
dependent representations. To ensure compatibility with parallel processing, we
designate the lowest bitrate representation as the reference representation.
The experimental results indicate a substantial improvement in the encoding
time for the dependent representations, achieving an average reduction of 40%,
while maintaining a minimal average quality drop of only 0.43 in Video
Multi-method Assessment Fusion (VMAF). This improvement is observed when
utilizing Versatile Video Encoder (VVenC), an open and optimized VVC encoder
implementation.
