Optimal and heuristic policies for dynamic server allocation

We examine a system where the servers in a cluster may be switched dynamically and preemptively from one kind of work to another. The demand consists of M job types joining separate queues, with different arrival and service characteristics, and also different relative importance represented by appropriate holding costs. The switching of a server from queue i to queue j incurs a cost which may be monetary or may involve a period of unavailability. The optimal switching policy is obtained numerically by solving a dynamic programming equation. Two simple heuristic policies-one static and one dynamic-are evaluated by simulation and are compared to the optimal policy. The dynamic heuristic is shown to perform well over a range of parameters, including changes in demand.