Peak Load Management for Commercial Web Servers using Adaptive Session-based Admission Control

In this paper, we use a session-based workload to measure a performance of a commercial web server. We dene a session as a sequence of client requests. An overloaded web server can experience a severe loss of throughput when measured as the number of completed sessions. Moreover, the overloaded web server discriminates against longer sessions. Session based admission control (SBAC), introduced in [2, 3], prevents a web server from becoming overloaded and ensures that longer sessions can be completed. We propose two new adaptive admission control strategies: hybrid and predictive, aiming to optimize the performance of SBAC mechanism. The hybrid strategy is based on a selftunable admission control function, which adjust itself accordingly to variations in tra c loads. It shows improved performance results for workloads with medium to long average session length. The predictive strategy estimates and predicts the number of new sessions it can accept and still guarantee processing of all future session requests. It consistently shows the best performance results for di erent workloads and di erent