DocumentCode
251844
Title
Loosely-Coupled Benchmark Framework Automates Performance Modeling on IaaS Clouds
Author
Xinni Ge ; Zhengwei Qi ; Ken Chen ; Jiangang Duan ; Zhenjiang Dong
fYear
2014
fDate
8-11 Dec. 2014
Firstpage
473
Lastpage
480
Abstract
Cloud computing is under rapid development, which brings the urgent need of evaluation and comparison of cloud systems. The performance testers often struggle in tedious manual operations, when carrying out lots of similar experiments on the cloud systems. However, few of current benchmark tools provide both flexible workflow controlling methodology and extensible workload abstraction at the same time. We present a modeling methodology to compare the performance from multiple aspects based on a loosely coupled benchmark framework, which automates experiments under agile workflow controlling and achieves broad cloud supports, as well as good workload extensibility. With several built-in workloads and scenario templates, we performed a series of tests on Amazon EC2 services and our private Open Stack-based cloud, and analyze the elasticity and scalability based on the performance models. Experiments show the robustness and compatibility of our framework, which makes remarkable guarantee that it can be leveraged in practice for researchers and testers to perform their further study.
Keywords
benchmark testing; cloud computing; public domain software; software prototyping; Amazon EC2 services; IaaS cloud systems; agile workflow control; automatic performance modeling; benchmark tools; cloud computing; cloud supports; elasticity analysis; extensible-workload abstraction; flexible-workflow control methodology; loosely-coupled benchmark framework; performance models; private OpenStack-based cloud; scalability analysis; scenario templates; workload templates; Benchmark testing; Cloud computing; Databases; Java; Parallel processing; Scalability; Throughput; cloud computing; measurement; performance analysis; performance modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Utility and Cloud Computing (UCC), 2014 IEEE/ACM 7th International Conference on
Conference_Location
London
Type
conf
DOI
10.1109/UCC.2014.60
Filename
7027527
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