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Overload protection is critical to E-commerce Web sites. This paper presents a profit-aware admission control mechanism for overload protection in E-commerce Web sites. Motivated by the observation [Measure Twice, Cut Once-Metrics For Online Retailers, 2006, (http://www.techexchange.com/thelibrary/online_retail_metrics.html)] that once a client made an initial purchase, the buy-to-visit ratio of the client escalates from less than 1% to nearly 21%, the proposed mechanism keeps track of the purchase records of clients and utilizes them to make admission control decisions. We build two hash tables with full IP address and network ID prefix, which maintain the purchase records of clients in fine-grain and coarse-grain manners, respectively. We classify those clients who made purchases before as premium customers and those clients without prior purchase behavior as basic customers. Under overload conditions, our mechanism differentiates premium customers from basic customers based on the record hash tables, and admits premium customers with much higher probability than basic customers. In favor of premium customers, our mechanism maximizes the revenues of E-commerce Web sites. We evaluate the efficacy of the profit-aware mechanism using the industry-standard TCP-W workloads. Our experimental results demonstrate that under overload conditions, the profit-aware admission control mechanism not only achieves higher throughput and lower response time, but also dramatically increases the revenue received by E-commerce Web sites.