Web Server Support for e-Customer Loyalty through QoS Differentiation

Abstract

The paper deals with the problem of offering predictive service in e-commerce Web server systems under overload. Due to unpredictability of Web accesses, such systems often fail to effectively handle peak traffic, which results in long delays and incomplete transactions. As a consequence, online retailers miss an opportunity to attract new customers, retain the loyalty of regular customers, and increase profits. We propose a method for priority-based admission control and scheduling of requests at the Web server system in order to differentiate Quality of Service (QoS) with regard to user-perceived delays, i.e., Web page response times provided by the system (as opposed to HTTP request response times). To detect and cope with the system overload, a new kind of a load indicator is proposed, based on online measurements of page response times. Simulation results demonstrate that our solution is capable of providing key customers with limited delays while improving QoS for ordinary customers under heavy load.