  In this paper, we study the capacity region of the general distributed index
coding. In contrast to the traditional centralized index coding where a single
server contains all $n$ messages requested by the receivers, in the distributed
index coding there are $2^n-1$ servers, each containing a unique non-empty
subset $J$ of the messages and each is connected to all receivers via a
noiseless independent broadcast link with an arbitrary capacity $C_J \ge 0$.
First, we generalize the existing polymatroidal outer bound on the capacity
region of the centralized problem to the distributed case. Next, building upon
the existing centralized composite coding scheme, we propose three distributed
composite coding schemes and derive the corresponding inner bounds on the
capacity region. We present a number of interesting numerical examples, which
highlight the subtleties and challenges of dealing with the distributed index
coding, even for very small problem sizes of $n=3$ and $n=4$.
