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Research on performance evaluation method of public cloud storage system
LI Ani, ZHANG Xiao, ZHANG Boyang, LIU Chunyi, ZHAO Xiaonan
Journal of Computer Applications    2017, 37 (5): 1229-1235.   DOI: 10.11772/j.issn.1001-9081.2017.05.1229
Abstract754)      PDF (1069KB)(603)       Save
With the rapid development and wide application of cloud storage system, many enterprise developers and individual users migrate their applications from traditional storage to public cloud storage system. Therefore, the performance of cloud storage system has become the focus of enterprise developers and individual users. The traditional test is difficult to simulate simultaneous access with enough users to the cloud storage system, complex to build and has a long test time with high cost. Besides, the evaluation results are unstable due to the network and other outside factors. In view of above critical problems, a kind of "cloud testing cloud" performance evaluation method was put forward for public cloud storage system. Public cloud storage system was evaluated by this method through applying a sufficient number of instances on the cloud computing platform. Firstly, a general performance evaluation framework was built with abilities such as dynamic instance application, automated deployment of assessment tools and load, controlling concurrent access to cloud storage system, automated instance release and evaluation results collection and feedback. Secondly, some multi-dimensional performance evaluation indicators were presented, covering different typical applications and different cloud storage interfaces. Finally, an extensible general performance evaluation model was put forward, which could evaluate the performance of typical applications, analyze the factors influencing cloud storage performance and be applied to any public cloud storage platform. In order to verify the feasibility, rationality, universality and expansibility of this method, these presented methods were applied to evaluate Amazon S3 cloud storage system, and then the accuracy of the evaluation results was verified by s3cmd. The results show that the evaluation output can provide reference comments for enterprise developers and individual users.
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