Distributed Resource Allocation Strategies for Achieving Quality of Service in Server Clusters

We investigate the resource allocation problem for large-scale server clusters with quality-of-service objectives, where key functions are decentralized. Specifically, the optimal service selection is posed as a discrete utility maximization problem that reflects management objectives and resource constraints. We develop an efficient centralized algorithm that solves this problem, and we propose three suboptimal schemes that operate with local information. The performance of the suboptimal schemes is evaluated in simulations, both under idealized conditions and in a full-scale system simulator