  A system manager dynamically controls a diffusion process Z that lives in a
finite interval [0,b]. Control takes the form of a negative drift rate \theta
that is chosen from a fixed set A of available values. The controlled process
evolves according to the differential relationship dZ=dX-\theta(Z) dt+dL-dU,
where X is a (0,\sigma) Brownian motion, and L and U are increasing processes
that enforce a lower reflecting barrier at Z=0 and an upper reflecting barrier
at Z=b, respectively. The cumulative cost process increases according to the
differential relationship d\xi =c(\theta(Z)) dt+p dU, where c(\cdot) is a
nondecreasing cost of control and p>0 is a penalty rate associated with
displacement at the upper boundary. The objective is to minimize long-run
average cost. This problem is solved explicitly, which allows one to also solve
the following, essentially equivalent formulation: minimize the long-run
average cost of control subject to an upper bound constraint on the average
rate at which U increases. The two special problem features that allow an
explicit solution are the use of a long-run average cost criterion, as opposed
to a discounted cost criterion, and the lack of state-related costs other than
boundary displacement penalties. The application of this theory to power
control in wireless communication is discussed.
