End-to-End Performance Prediction for Selecting Cloud Services Solutions

被引:5
|
作者
Karim, Raed [1 ]
Ding, Chen [1 ]
Miri, Ali [1 ]
机构
[1] Ryerson Univ, Dept Comp Sci, 350 Victoria St, Toronto, ON M5B 2K3, Canada
来源
9TH IEEE INTERNATIONAL SYMPOSIUM ON SERVICE-ORIENTED SYSTEM ENGINEERING (SOSE 2015) | 2015年
关键词
QoS; IaaS; SaaS; End-to-End Cloud Performance Prediction; Cloud Computing;
D O I
10.1109/SOSE.2015.11
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In cloud computing, in order to select or recommend the best service solutions to end users, the end-to-end QoS requirements (e.g. response time and throughput) have to be computed. A typical cloud solution is a combination of multiple component services such as IaaS, SaaS, PaaS, etc. In a simplified case, there could be two components-software services and infrastructure services. The software service alone can satisfy end user's functional requirements (e.g. business objectives); however, the end-to-end QoS requirements require a collaboration of the multiple components at multiple cloud layers. In this paper, we consider the multilayered cloud architecture for computing the end-to-end performance values for cloud solutions. We propose a new method for measuring cloud component services similarity and predicting the end-to-end performance values of cloud solutions. In this method, the historical performance data of cloud component services is used based on users' past invocations. To evaluate our method and show its effectiveness, series of experiments are conducted. The experimental results demonstrate that our cloud multi-layers based method produces better prediction accuracy than other prediction approaches that consider one cloud layer.
引用
收藏
页码:69 / 77
页数:9
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