  The dimensioning of caching systems represents a difficult task in the design
of infrastructures for content distribution in the current Internet. This paper
addresses the problem of defining a realistic arrival process for the content
requests generated by users, due its critical importance for both analytical
and simulative evaluations of the performance of caching systems. First, with
the aid of YouTube traces collected inside operational residential networks, we
identify the characteristics of real traffic that need to be considered or can
be safely neglected in order to accurately predict the performance of a cache.
Second, we propose a new parsimonious traffic model, named the Shot Noise Model
(SNM), that enables users to natively capture the dynamics of content
popularity, whilst still being sufficiently simple to be employed effectively
for both analytical and scalable simulative studies of caching systems.
Finally, our results show that the SNM presents a much better solution to
account for the temporal locality observed in real traffic compared to existing
approaches.
