State Space Model and Queuing Network Based Cloud Resource Provisioning for Meshed Web Systems

Functions provided byWeb applications are increasingly diverse which make their structures complicated and meshed. Cloud computing platforms provide elastic computing capacities for these meshedWeb systems to guarantee Service Level Agreement (SLA). Though workloads of meshedWeb systems usually change steadily and periodically in total, sometimes there are sudden fluctuations. In this paper, a hybrid State-space-model-and-Queuing-network based Feedback control method (SQF) is developed for auto-scaling Virtual Machines (VMs) allocated to each tier of meshedWeb systems. For the case with workloads changing steadily, a State-spacemodel based static Feedback Control method (SFC) is proposed in SQF to stabilize request response times near the reference time. For unsteadily changing workloads, a Queuing-network based multi-tier collaborative Feedback Control method (QFC) is proposed for effectively eliminating bottlenecks. QFC builds a control systemfor each tier individually and uses the queuing network to measure the interaction relationships among different tiers. Experimental results show that QFC is able to improve the efficiency of eliminating bottlenecks (decreasing upper-limit SLAviolation ratios by 31.99%similar to 56.52%) with similar or a little bit high VM rental costs compared to existing methods while SFC obtains more stable response times for requests with reasonable additional costs.