  We introduce optimal algorithms for the problems of data placement (DP) and
page placement (PP) in networks with a constant number of clients each of which
has limited storage availability and issues requests for data objects. The
objective for both problems is to efficiently utilize each client's storage
(deciding where to place replicas of objects) so that the total incurred access
and installation cost over all clients is minimized. In the PP problem an extra
constraint on the maximum number of clients served by a single client must be
satisfied. Our algorithms solve both problems optimally when all objects have
uniform lengths. When objects lengths are non-uniform we also find the optimal
solution, albeit a small, asymptotically tight violation of each client's
storage size by $\epsilon$lmax where lmax is the maximum length of the objects
and $\epsilon$ some arbitrarily small positive constant. We make no assumption
on the underlying topology of the network (metric, ultrametric etc.), thus
obtaining the first non-trivial results for non-metric data placement problems.
