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The dimensioning of caching systems represents a difficult task in the designof infrastructures for content distribution in the current Internet. This paperaddresses the problem of defining a realistic arrival process for the contentrequests generated by users, due its critical importance for both analyticaland simulative evaluations of the performance of caching systems. First, withthe aid of YouTube traces collected inside operational residential networks, weidentify the characteristics of real traffic that need to be considered or canbe 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 contentpopularity, whilst still being sufficiently simple to be employed effectivelyfor both analytical and scalable simulative studies of caching systems.Finally, our results show that the SNM presents a much better solution toaccount for the temporal locality observed in real traffic compared to existingapproaches.

Temporal Locality in Today's Content Caching: Why it Matters and How to Model it