eQoS: Provisioning of Client-Perceived End-to-End QoS Guarantees in Web Servers

It is important to guarantee client-perceived end-to-end quality of service (QoS) under heavy load conditions. Existing work focuses on network transfer time or server-side request processing time. In this paper, we propose a novel framework, eQoS, to monitor and control client-perceived response time in heavy loaded Web servers. The response time is measured with respect to Web pages that contain multiple embedded objects. Within the framework, we propose an adaptive fuzzy controller, STFC, to allocate server resources. The controller assumes no knowledge of the pageview traffic model. It deals with the effect of process delay in resource allocation by its two-level self-tuning capabilities. We also prove the stability of the STFC. We implement a prototype of eQoS in Linux and conduct comprehensive experiments across wide-range server workload conditions on PlanetLab and simulated networks. Experimental results demonstrate the effectiveness of the framework: it controls the deviation of client-perceived pageview response time to be within 20 percent of a predefined target with both synthetic and real Web traffics. We also compare the STFC with other controllers, including static fuzzy, linear proportional integral (PI), and adaptive PI controllers. Experimental results show that, although the STFC works slightly worse than the static fuzzy controller in the environment where the static fuzzy controller is best tuned, because of its self-tuning capabilities, it has better performance in all other test cases by around 25 percent on average in terms of the deviation from the target response time. In addition, due to its model independence, the STFC outperforms the linear PI and adaptive PI controllers by 50 percent and 75 percent on average, respectively