Model-based methods for quality evaluation of cloud services

被引:1
|
作者
Adiththan, Arun [1 ]
Ravindran, Kaliappa [2 ]
机构
[1] Gen Motors Populus Grp, Warren, MI 48092 USA
[2] CUNY, New York, NY 10031 USA
关键词
D O I
10.1109/DASC/PiCom/CBDCom/CyberSciTech.2019.00130
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The issue of less-than-100% reliability and trustworthiness of third-party controlled cloud components (e.g., IaaS and SaaS components from different vendors) may lead to laxity in the QoS guarantees offered by a service-support system S to various applications. Our goal is to assess how well the internal mechanisms of S are geared to offer a required level of service, to the applications. Our external assessment of QoS provisioning involves the construction of a computational model of the actual system under test. We employ system identification technique that uses the computational model to determine the feasible resource allocation for an externally observed behavior and use it to infer the actual system parameters. Our external system assessment methodology delineates domain-knowledge of the system from the assessment process at a meta-level and hence allows re-use of the technique across different systems, We illustrate our QoS assessment method using a replicated data service case study.
引用
收藏
页码:687 / 692
页数:6
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