Emergent Mind

Content Caching for Shared Medium Networks Under Heterogeneous Users' Behaviours

(2105.03220)
Published May 7, 2021 in cs.IT , cs.NI , and math.IT

Abstract

Content caching is a widely studied technique aimed to reduce the network load imposed by data transmission during peak time while ensuring users' quality of experience. It has been shown that when there is a common link between caches and the server, delivering contents via the coded caching scheme can significantly improve performance over conventional caching. However, finding the optimal content placement is a challenge in the case of heterogeneous users' behaviours. In this paper we consider heterogeneous number of demands and non-uniform content popularity distribution in the case of homogeneous and heterogeneous user preferences. We propose a hybrid coded-uncoded caching scheme to trade-off between popularity and diversity. We derive explicit closed-form expressions of the server load for the proposed hybrid scheme and formulate the corresponding optimization problem. Results show that the proposed hybrid caching scheme can reduce the server load significantly and outperforms the baseline pure coded and pure uncoded and previous works in the literature for both homogeneous and heterogeneous user preferences.

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