Drift rate control of a brownian processing system

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Abstract

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 θ that is chosen from a fixed set A of available values. The controlled process evolves according to the differential relationship dZ = dX - θ(Z) dt + dL - dU, where X is a (0, σ) Brownian motion, and L and U arc 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 dξ = c(θ(Z)) dt + p dU, where c(·) is a non-decreasing 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.

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Ata, B., Harrison, J. M., & Shepp, L. A. (2005). Drift rate control of a brownian processing system. Annals of Applied Probability, 15(2), 1145–1160. https://doi.org/10.1214/105051604000000855

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