Resource Allocation with Stochastic Demands

Resources in modern computer systems include not only CPU, but also memory, hard disk, bandwidth, etc. To serve multiple users simultaneously, we need to satisfy their requirements in all resource dimensions. Meanwhile, their demands follow a certain distribution and may change over time. Our goal is then to admit as many users as possible to the system without violating the resource capacity more often than a predefined overflow probability. In this paper, we study the problem of allocating multiple resources among a group of users/tasks with stochastic demands. We model it as a stochastic multi-dimensional knapsack problem. We extend and apply the concept of effective bandwidth in order to solve this problem efficiently. Via numerical experiments, we show that our algorithms achieve near-optimal performance with specified overflow probability.

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