@article{Biju R Mohan_G Ram Mohana Reddy_2017, title={LIFE DATA ANALYSIS OF SERVER VIRTUALIZED SYSTEM}, volume={13}, url={https://geomatejournal.com/geomate/article/view/3040}, abstractNote={<p>The use of reliability metrics and life data analysis has received considerable attention<br>recently in the software engineering literature. Life data analysis under the actual operational profile can,<br>however, be expensive, time consuming or even infeasible. In this paper, a systematic approach has been<br>adopted in order to reduce the experimentation time for estimating time to failure of a server virtualized<br>system. The study of time to failure (TTF) is very essential in server virtualized system, because it is the crux<br>of the cloud computing infrastructure. In order to meet service-level agreements (SLAs) like availability,<br>reliability and response time, prediction of reliability metrics like mean time to failure (MTTF), life<br>distribution etc are indispensable. The most important contributions of this paper are the reduction of<br>experimental time, and the life data analysis of the server virtualized systems which were not addressed so far.<br>Experimental results demonstrate that there is only four percentage deviation from the observed results from<br>the Normalized Root Mean Square Error and resulting in 96% accuracy of predicting MTTF.</p>}, number={36}, journal={GEOMATE Journal}, author={Biju R Mohan and G Ram Mohana Reddy}, year={2017}, month={Aug.}, pages={108–115} }