Fluid modeling and control for server system performance and availability

Abstract

Although server technology provides a means to support a wide range of online services and applications, their ad-hoc configuration poses significant challenges to the performance, availability and economical costs of applications. In this paper, we examine the impact of server configuration on the central tradeoff between service performance and availability. First, we present a server model as a nonlinear continuous-time model using fluid approximations. Second, we develop admission control of server systems for an optimal configuration. We provide two control laws for two different QoS objectives. AM-C is an availability-maximizing admission control that achieves the highest service availability given a fixed performance constraint; and PM-C is a performance-maximizing admission control that meets a desired availability target with the highest performance. We evaluate our fluid model and control techniques on the TPC-C industry-standard benchmark. Our experiments show that the proposed techniques improve performance by up to 30 % while guaranteeing availability constraints.