Scalability analysis comparisons of cloud-based software services

被引:0
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作者
Amro Al-Said Ahmad
Peter Andras
机构
[1] Keele University,School of Computing and Mathematics
[2] Philadelphia University,Faculty of Information Technology
关键词
Measurement; Performance; Scalability; Software-as-a-service (SaaS); Metrics;
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摘要
Performance and scalability testing and measurements of cloud-based software services are necessary for future optimizations and growth of cloud computing. Scalability, elasticity, and efficiency are interrelated aspects of cloud-based software services’ performance requirements. In this work, we use a technical measurement of the scalability of cloud-based software services. Our technical scalability metrics are inspired by metrics of elasticity. We used two cloud-based systems to demonstrate the usefulness of our metrics and compare their scalability performance in two cloud platforms: Amazon EC2 and Microsoft Azure. Our experimental analysis considers three sets of comparisons: first we compare the same cloud-based software service hosted on two different public cloud platforms; second we compare two different cloud-based software services hosted on the same cloud platform; finally, we compare between the same cloud-based software service hosted on the same cloud platform with two different auto-scaling policies. We note that our technical scalability metrics can be integrated into a previously proposed utility oriented metric of scalability. We discuss the implications of our work.
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