You Really Need A Good Ruler to Measure Caching Performance in Information-Centric Networks

Abstract: 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.