  Joint caching and recommendation has been recently proposed for increasing
the efficiency of mobile edge caching. While previous works assume
collaboration between mobile network operators and content providers (who
control the recommendation systems), this might be challenging in today's
economic ecosystem, with existing protocols and architectures. In this paper,
we propose an approach that enables cache-aware recommendations without
requiring a network and content provider collaboration. We leverage information
provided publicly by the recommendation system, and build a system that
provides cache-friendly and high-quality recommendations. We apply our approach
to the YouTube service, and conduct measurements on YouTube video
recommendations and experiments with video requests, to evaluate the potential
gains in the cache hit ratio. Finally, we analytically study the problem of
caching optimization under our approach. Our results show that significant
caching gains can be achieved in practice; 8 to 10 times increase in the cache
hit ratio from cache-aware recommendations, and an extra 2 times increase from
caching optimization.
