In this paper we develop an analytical framework, based on the Che approximation \mbox{%DIFAUXCMD che Least Recently Used (LRU) caches operating under the Shot Noise requests Model (SNM). The SNM was recently proposed in \mbox{%DIFAUXCMD nostroCCR to better capture the main characteristics of today Video on Demand ( Vod ) traffic. In this context, the Che approximation is derived as the application of a mean field principle to the cache eviction time. We investigate the validity of this approximation through an asymptotic analysis of the cache eviction time. Particularly , we provide a large deviation principle  and a central limit theorem for the cache eviction time, as the cache size grows large. Furthermore, we obtain a non-asymptotic analytical upper bound on the error entailed by Che's approximation of the hit probability .
In this paper we analyze Least Recently Used (LRU) caches operating under the Shot Noise requests Model (SNM). The SNM was recently proposed to better capture the main characteristics of today Video on Demand ( VoD ) traffic. We investigate the validity of Che's approximation through an asymptotic analysis of the cache eviction time. In particular , we provide a large deviation principle , a law of large numbers and a central limit theorem for the cache eviction time, as the cache size grows large. Finally, we derive upper and lower bounds for the "hit" probability in tandem networks of caches under Che's approximation .
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In this context, the Che approximation is derived as the application of a mean field principle to the cache eviction time.
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Furthermore, we obtain a non-asymptotic analytical upper bound on the error entailed by
Finally, we derive upper and lower bounds for the "hit" probability in tandem networks of caches under
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of the hit probability