  Information-centric networks are an interesting new paradigm for distributing
content on the Internet. They bring up many research challenges, such as
addressing content by name, securing content, and wide-spread caching of
content. Caching has caught a lot of attention in the research community, but a
lot of the work suffers from a poor understanding of the different metrics with
which caching performance can be measured. In this paper we not only present a
comprehensive overview of different caching metrics that have been proposed for
information-centric networks, but also propose the coupling factor as a new
metric to capture the relation- ship between content popularity and network
topology. As we show, many commonly used metrics have several failure modes
which are largely ignored in literature. We identify these problems and propose
remedies and new metrics to address these failures. Our work highlights the
fundamental differences between information-centric caches and "traditional"
cache networks and we demonstrate the need for a systematic understanding of
the metrics for information- centric caching. We also discuss how experimental
work should be done when evaluating networks of caches.
