Stochastic Dynamic Cache Partitioning for Encrypted Content Delivery
Résumé
In-network caching is an appealing solution to
cope with the increasing bandwidth demand of video, audio
and data transfer over the Internet. Nonetheless, an increasing
share of content delivery services adopt encryption through
HTTPS, which is not compatible with traditional ISP-managed
approaches like transparent and proxy caching. This raises the
need for solutions involving both Internet Service Providers
(ISP) and Content Providers (CP): by design, the solution
should preserve business-critical CP information (e.g., content
popularity, user preferences) on the one hand, while allowing for
a deeper integration of caches in the ISP architecture (e.g., in
5G femto-cells) on the other hand.
In this paper we address this issue by considering a content-
oblivious ISP-operated cache. The ISP allocates the cache storage
to various content providers so as to maximize the bandwidth
savings provided by the cache: the main novelty lies in the fact
that, to protect business-critical information, ISPs only need to
measure the aggregated miss rates of the individual CPs and
does not need to be aware of the objects that are requested, as
in classic caching. We propose a cache allocation algorithm based
on a perturbed stochastic subgradient method, and prove that
the algorithm converges close to the allocation that maximizes the
overall cache hit rate. We use extensive simulations to validate
the algorithm and to assess its convergence rate under stationary
and non-stationary content popularity. Our results (i) testify
the feasibility of content-oblivious caches and (ii) show that the
proposed algorithm can achieve within 10% from the global
optimum in our evaluation.