over an orthogonal frequency band, the requests can be delivered in parallel, and the delivery latency is given by $T_{pd}=\max_{p} R_p$. If, instead, the servers transmit successively in a time-division manner, which is suitable for user devices that are simple and not capable of multihoming on multiple frequencies, the normalized delivery latency will be given by $T_{sd}=\sum_{p=1}^{P} R_p$. Our goal will be to find the average worst-case delivery latency, where the worst case refers to the fact that all the users can correctly decode their requested files, independent of the combination of files requested by them, and the averaging is over all possible network topologies. Assuming that $N\geq K$ (i.e., the number of files is larger than the number of users), it is not difficult to see that all the users requesting a different file corresponds to the worst-case scenario. We would also like to remark that, under uniform file popularity, the probability of experiencing this worst-case demand distribution increases significantly with $N$, and approaches $1$ for $N$ values that one expects to experience in practice.

Coded Distributed Storage and Caching Scheme
============================================

We first note that our system model brings together aspects of distributed storage and proactive caching/coded delivery. 