An Integrated Adaptive Management System for Cluster-based Web Services

The complexity of the cluster-based Web service challenges the traditional approaches, which fail to guarantee the reliability and real-time performance required. In this paper, we present an integrated adaptive management system (JAMS) for such service. The issues we discuss address to efficiently allocate resources and provide more effective QoS support under a wide range of load conditions. For the global resource level, we introduce spare instance and corresponding management strategy as a supplemental adaptive mechanism. The spare instances hosted on shared node afford better resource utilization and more effective QoS support in the case of overload or workload fluctuation. Further, it can relax the influence of the fault recovery from the hardware and software failure. For the local level, we apply a multipurpose linear-quadratic regulator (LQR) as basic adaptive element. The control scheme using reject time ratio as control input is able to provide guarantees for overload protection, resource control, Qos control, performance isolation, and effective management for spare instances. Results of experiments on both static and dynamic Web sites illustrate the efficiency and robustness of the multi-purpose LQR