Cluster Computing

, Volume 22, Supplement 5, pp 11307–11317 | Cite as

CCMA—cloud critical metric assessment framework for scientific computing

  • V. G. RavindhrenEmail author
  • S. Ravimaran


Cloud Computing has become the preferred choice of performing scientific applications over the cloud since the computing has become as a utility. Cloud-based services have evolved exponentially and also the sophistication of Cloud infrastructure supporting these services has grown. Running traditional applications such as scientific data processing on Cloud, needs to consider the suitability of the could for the compliance of the Cloud critical metrics. This article aims to study the performance of public clouds to support the scientific computing, which were performed on Grid computing, High performance computing or cluster computing. This article tries to address the issue by designing and developing a framework to measure the critical metrics. The performance of the public clouds was assessed through probing, simulation and historic data. The results indicate that only a few provide heterogeneous cloud services. Performance of some of the clouds services can be improved by tweaking the critical metrics.


Cloud computing Performance analysis Performance metrics Service measurement Service monitoring 


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© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of Computer EngineeringSeshasayee Institute of TechnologyTiruchirappalliIndia
  2. 2.Software System Group Lab, M.A.M. College of EngineeringAnna UniversityChennaiIndia

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