  We consider the distributed function computation problem in asymmetric
communication scenarios, where the sink computes some deterministic function of
the data split among N correlated informants. The distributed function
computation problem is addressed as a generalization of distributed source
coding (DSC) problem. We are mainly interested in minimizing the number of
informant bits required, in the worst-case, to allow the sink to exactly
compute the function. We provide a constructive solution for this in terms of
an interactive communication protocol and prove its optimality. The proposed
protocol also allows us to compute the worst-case achievable rate-region for
the computation of any function. We define two classes of functions: lossy and
lossless. We show that, in general, the lossy functions can be computed at the
sink with fewer number of informant bits than the DSC problem, while
computation of the lossless functions requires as many informant bits as the
DSC problem.
