Cache Content Selection Policies for Streaming Video Services

The majority of internet traffic is now dominated
by streamed video content. As video quality continues to increase,
the strain that streaming traffic places on the network
infrastructure also increases. Caching content closer to users, e.g.,
using Content Distribution Networks, is a common solution to
reduce the load on the network. A simple approach to selecting
what to put in regional caches is to put the videos that are
most popular globally across the entire customer base. However,
this approach ignores distinct regional taste. In this paper we
explore the question of how a video content provider could go
about determining whether or not they should use a cache filling
policy based solely upon global popularity or take into account
regional tastes as well. We propose a model that captures the
overlap between inter-regional and intra-regional preferences. We
focus on movie content and derive a synthetic model that captures
“taste” using matrix factorization, similarly to the method used
in recommender systems. Our model enables us to widely explore
the parameter space, and derive a set of metrics providers can
use to determine whether populating caches according to regional
of global tastes provides better cache performance.

• Networking