  Recent studies into streaming media delivery suggest that performance gains
from cache hierarchies such as Information-Centric Networks (ICNs) may be
negated by Dynamic Adaptive Streaming (DAS), the de facto method for retrieving
multimedia content. The bitrate adaptation mechanisms that drive video
streaming clash with caching hierarchies in ways that affect users' Quality of
Experience (QoE). Cache performance also diminishes as consumers dynamically
select content encoded at different bitrates. In this paper we use the evidence
to draw a novel insight: in a cache hierarchy for adaptive streaming content,
bitrates should be prioritized over or alongside popularity and hit rates. We
build on this insight to propose RippleCache as a family of cache placement
schemes that safeguard high-bitrate content at the edge and push low-bitrate
content into the network core. Doing so reduces contention of cache resources,
as well as congestion in the network. To validate RippleCache claims we
construct two separate implementations. We design RippleClassic as a benchmark
solution that optimizes content placement by maximizing a measure for cache
hierarchies shown to have high correlation with QoE. In addition, our
lighter-weight RippleFinder is then re-designed with distributed execution for
application in large-scale systems. RippleCache performance gains are
reinforced by evaluations in NS-3 against state-of-the-art baseline approaches,
using standard measures of QoE as defined by the DASH Industry Forum.
Measurements show that RippleClassic and RippleFinder deliver content that
suffers less oscillation and rebuffering, as well as the highest levels of
video quality, indicating overall improvements to QoE.
