AERS: An Autonomic and Elastic Resource Scheduling Framework for Cloud Applications
Jianyun Sun, Haopeng Chen, Zhida Yin · 2016
The elasticity of cloud computing is able to help Cloud Application Providers (CAPs) adjust the number of rented virtual machines (VMs) for cloud applications according to actual varying demands while enforcing SLAs. In this paper, we design a framework called AERS (Autonomic and Elastic Resource Scheduling Framework). AERS makes full use of the profits of both proactive controllers and reactive controllers in the field of dynamic resource provision. It can not only adjust the number of available VMs for cloud applications with fluctuation of workloads but also react fast when cloud applications break SLAs. In addition, We build a model for the availability of cloud applications. Based on this model, we propose an availability-aware and communication overhead optimized placement strategy integrated in AERS to help CAPs choose proper availability zones for launching VMs. Experiments on Openstack show that AERS is able to provide VMs elastically while enforcing SLAs.