to the best-case performance, which is the single-server centralized delivery latency derived in[@maddah], achieved when all the users connect to the same set of servers, maximizing the multicasting opportunities. We observe that, as the server storage capacities increase, the average delivery latency vs. user cache memory trade-off improves, approaching the single-server performance. We give an analytical expression to compute the average delivery latency for different server storage capacities, which is shown to give a fairly accurate estimate of the expected delivery latency when the number of servers is large. We then consider the delivery latency when the servers can transmit in parallel. We characterize the achievable average worst case delivery latency of the proposed coded storage and delivery scheme as a function of the server storage capacity for different $\rho$ values.

In a related work [@Vaneet], the authors study coded caching schemes presented in [@maddah] and [@chao] when parity servers are available. The authors consider special scenarios with one and two parity servers. They propose a scheme that stripes the files into blocks, and codes them across the servers with a systematic MDS code, and they also propose a scheme for the scenario in which files are stored as whole 