International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 179 - Issue 33 |
Published: Apr 2018 |
Authors: Stephen M. Ciirah, Andrew M. Kahonge, Elisha O. Abade |
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Stephen M. Ciirah, Andrew M. Kahonge, Elisha O. Abade . Cloud Computing: An Empirical Study of the Correlation between Scalability and Throughput of Cloud-based Applications. International Journal of Computer Applications. 179, 33 (Apr 2018), 10-17. DOI=10.5120/ijca2018916741
@article{ 10.5120/ijca2018916741, author = { Stephen M. Ciirah,Andrew M. Kahonge,Elisha O. Abade }, title = { Cloud Computing: An Empirical Study of the Correlation between Scalability and Throughput of Cloud-based Applications }, journal = { International Journal of Computer Applications }, year = { 2018 }, volume = { 179 }, number = { 33 }, pages = { 10-17 }, doi = { 10.5120/ijca2018916741 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2018 %A Stephen M. Ciirah %A Andrew M. Kahonge %A Elisha O. Abade %T Cloud Computing: An Empirical Study of the Correlation between Scalability and Throughput of Cloud-based Applications%T %J International Journal of Computer Applications %V 179 %N 33 %P 10-17 %R 10.5120/ijca2018916741 %I Foundation of Computer Science (FCS), NY, USA
The goal of this research was to investigate how application architecture impacts the performance of cloud-based applications. One specific area of examination was to determine the correlation between throughput and scalability of applications in a cloud computing environment. The experimental methodology was adopted for the study. Microsoft Azure cloud platform and Microsoft Visual Studio Team Services were used to conduct graduated load performance tests. A convenience sample for the experiment consisted of seventeen web applications. Advanced statistical analysis of the results was conducted using Pearson Correlation Coefficient analysis. The results revealed that there was a strong positive correlation between throughput and scalability of cloud based applications, which was statistically significant. Therefore, through the experimental methodology, the null hypothesis was rejected and the alternative hypothesis was accepted.