Optimal dynamic scheduling in a multiclass fluid model of Internet servers with transient overload

Abstract

We consider the optimal dynamic scheduling of different requests of service in a multiclass stochastic fluid model that is motivated by recent and emerging computing paradigms for Internet services and applications. Our primary focus is on environments with specific performance guarantees for each class under a profit model in which revenues are gained when performance guarantees are satisfied and penalties are incurred otherwise. Within the context of the corresponding fluid model, we explore the dynamic scheduling of different classes of service under conditions where the workload of certain classes may be overloaded for a transient period of time. In particular, we consider the case with two fluid classes and a single server whose capacity can be shared arbitrarily among the two classes. Under the assumptions that the class 1 arrival rate varies with time and the class 1 fluid can more efficiently reduce the holding cost, we determine the optimal server allocation policy that minimizes the holding cost in the fluid model when the arrival rate function for class 1 is known. Using the key insights gained from this deterministic case, we also develop heuristic policies for the stochastic fluid system when the arrival rate function for class 1 is random.