Unequal‐interval based loosely coupled control method for auto‐scaling heterogeneous cloud resources for web applications

Abstract

Most existing quality of service (QoS) control algorithms of Web applications take into account Web Server or database connections which can be released immediately. However, many applications are deployed on virtual machines (VMs) or even Spot VMs elastically rented from public Clouds. To save costs, interval-priced VMs are not released until the ends of rented intervals. Such delays of control effects make existing methods rent or release excess VMs leading to overcontrol. Fluctuated prices make Spot VMs unreliable due to unexpected termination which makes fault-tolerant strategies crucial. In this article, an unequal-interval-based loosely coupled control method is proposed to improve the quality of service (QoS) control ability of fault-tolerant strategies. A queuing model with arrival-rate-adjustment coefficient is used to predict required capacity as a feedforward controller. Another two-threshold and queuing-model-based method is applied to update the coefficient as a loosely coupled feedback controller. Meanwhile, unequal-interval controller collaborating method is proposed to avoid overcontrol and react quickly to workload changes. Our approach is evaluated on both a simulation platform and a real Kubernetes Cluster. Experimental results illustrate that our approach decreases the percentage of waiting times larger than service level agreements with similar or lower rental costs compared with existing algorithms. K E Y W O R D S Cloud computing, feedback control, queuing model, resource provisioning, Spot VM 1 INTRODUCTION Cloud computing offers subscription-oriented services and it is widespread to rent Cloud virtual machines (VMs) elastically to support the running of Web applications. 1,2 VMs are generally priced by time intervals and the hour-based pricing model is especially popular in modern commercial public Clouds. Prices of On-demand VMs of Amazon EC2, Microsoft Azure, Aliyun, and so on are fixed. On the contrary, prices of Spot VMs of Amazon EC2 3,4 are dynamic because Spot VMs are auctioned by public Clouds. Spot VMs are cheaper than On-demand VMs but unreliable due to lease terminations when the current market price becomes higher than the bid. Most existing QoS control methods for Web applications only focus on resources inside one server or On-demand VMs. However, it is beneficial to rent Spot VMs to decrease VM rental costs. The principal goal of this article is to provision Spot and On-demand VMs elastically to minimize resource rental cost while guaranteeing the average waiting time of requests and

Emerging intelligent big data analytics for cloud and edge computing

“…Fluctuating prices make Spot VMs unreliable due to unexpected termination which makes fault‐tolerant strategies crucial. In order to decrease the VM rental cost while guaranteeing the SLA and robustness, Cai et al 4 proposed a hybrid control method UCM which takes advantage of queuing‐model‐based loosely coupled controllers, unequal‐interval‐based collaborating method, and an existing group‐based fault tolerant strategy.…”