Stochastic coded caching networks: A study of cache-load imbalance and random user activity

In this thesis, we elevate coded caching from their purely information-theoretic framework to a stochastic setting where the stochasticity of the networks originates from the heterogeneity in users’ request behaviors. Our results highlight that stochasticity in the cache-aided networks can lead to the vanishing of the gains of coded caching. We determine the exact extent of the cache-load imbalance bottleneck of coded caching in stochastic networks, which has never been explored before. Our work provides techniques to mitigate the impact of this bottleneck for the scenario where the user-to-cache state associations are restricted by proximity constraints between users and helper nodes (i.e., shared-cache setting) as well as for the scenario where user-to-cache state associations strategies are considered, as a design parameter (i.e. subpacketization-constrained setting).