Demand-driven Service Differentiation for Cluster-based Network Servers

Service differentiation that provides prioritized service qualities to multiple classes of client requests can effectively utilize available server resources. This paper studies how demand-driven service differentiation with admission control can be supported in cluster-based network services. Our objective is to provide better services to high priority request classes without over-sacrificing low priority classes. To achieve this objective, we propose a dynamic scheduling scheme that adapts to varying request resource demands and periodically repartitions servers. This scheme also employs priority-based admission control to drop excessive user requests and achieve soft performance guarantees. For each scheduling period, our scheme monitors the system status and uses a queuing model to approximate server behaviors and guide resource allocation. Our experiments show that the proposed technique achieves demand-driven service differentiation while maximizing resource utilization and that it can substantially outperform static server partitioning.