Accurately modeling workload interactions for deploying prefetching in Web servers

Although Web prefetching is regarded as an effective method to improve client access performance, the associated overhead prevents it from being widely deployed. Specifically, a major weakness in existing Web servers is that prefetching activities are scheduled independently of dynamically changing server workloads. Without proper control and coordination between the two kinds of activities, prefetching can negatively affect the Web services and degrade Web access performance. We first develop an open queuing model to characterize detailed transactions in Web servers. Using this model, we analyze server resource utilization and average response time with different request arrival rates when prefetching is involved under different kinds of Web services. Guided by this model, we then design a responsive and adaptive prefetching scheme that dynamically adjusts the prefetching aggressiveness in Web servers. Our scheme not only prevents the Web servers from being overloaded, but it can also minimize the average server response time. We have effectively implemented this scheme on an Apache Web server. Our measurement-based performance evaluation shows our model can accurately predict the utilization of Web server resources and the correspondent average response time