Self-Through Self-Learning: Overload Control for Distributed Web Systems
Overload control is a challenging problem for web-based applications, which are often prone to unexpected surges of traffic. Existing solutions are still far from guaranteeing the necessary responsiveness under rapidly changing operative conditions. The authors contribute an original Self-Overload Control (SOC) algorithm that self-configures a dynamic constraint on the rate of incoming new sessions in order to guarantee the fulfillment of the quality requirements specified in a Service Level Agreement (SLA). Their algorithm is based on a measurement activity that makes the system capable of self-learning and self-configuring even in the case of rapidly changing traffic scenarios, dynamic resource provisioning or server faults.