计算机科学
供应
排队论
云计算
分布式计算
状态空间
排队延迟
队列管理系统
计算机网络
操作系统
统计
数学
作者
Yamin Lei,Zhicheng Cai,Xiaoping Li,Rajkumar Buyya
出处
期刊:IEEE Transactions on Parallel and Distributed Systems
[Institute of Electrical and Electronics Engineers]
日期:2022-04-27
卷期号:33 (12): 3787-3799
标识
DOI:10.1109/tpds.2022.3170834
摘要
Functions provided by Web applications are increasingly diverse which make their structures complicated and meshed. Cloud computing platforms provide elastic computing capacities for these meshed Web systems to guarantee Service Level Agreement (SLA). Though workloads of meshed Web 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 meshed Web systems. For the case with workloads changing steadily, a State-space-model 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 system for 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 SLA violation ratios by 31.99% $\sim$ 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.
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