  Coded caching techniques have received significant attention lately due to
their provable gains in reducing the cost of data delivery in wireless
networks. These gains, however, have only been demonstrated under the
assumption of a free placement phase. This unrealistic assumption poses a
significant limitation, especially in cases where aggressive placement
strategies can lead to a significant transmission cost that may even be higher
than the corresponding cost of the delivery phase. In this paper, we relax this
assumption and propose a general caching framework that captures the
transmission cost of the two phases, and hence, results in minimizing the
overall rate of the caching network. We model the dynamic nature of the network
through a cost structure that allows for varying the network architecture and
cost per transmission, across the placement and delivery phases. We start with
the scenario where the individual users have no limit on the available caching
memory and characterize the jointly optimal solution as a function of the
different parameters in our cost structure. Then, we characterize the effect of
memory constraints on the optimal solution in certain special cases.
Interestingly, our results identify regions where the uncoded caching scheme
outperforms its coded counterpart. Further, coded caching is shown to offer
performance gains only when the network architecture during the placement phase
is different from that during the delivery phase.
