000			01719naaaa2200337uu 4500
001			https://directory.doabooks.org/handle/20.500.12854/53685
005			20220220033448.0
020			_aKSP/1000046300
020			_a9783731503590
024	7		_a10.5445/KSP/1000046300 _cdoi
041	0		_aEnglish
042			_adc
100	1		_aNoorshams, Omar-Qais _4auth
245	1	0	_aModeling and Prediction of I/O Performance in Virtualized Environments
260			_bKIT Scientific Publishing _c2017
300			_a1 electronic resource (XVIII, 276 p. p.)
506	0		_aOpen Access _2star _fUnrestricted online access
520			_aWe present a novel performance modeling approach tailored to I/O performance prediction in virtualized environments. The main idea is to identify important performance-influencing factors and to develop storage-level I/O performance models. To increase the practical applicability of these models, we combine the low-level I/O performance models with high-level software architecture models. Our approach is validated in a variety of case studies in state-of-the-art, real-world environments.
540			_aCreative Commons _fhttps://creativecommons.org/licenses/by-sa/4.0/ _2cc _4https://creativecommons.org/licenses/by-sa/4.0/
546			_aEnglish
653			_aModell
653			_aVorhersage
653			_aPerformanz
653			_aPrediction
653			_aI/O
653			_aVirtualisierungModel
653			_aPerformance
653			_aVirtualization
856	4	0	_awww.oapen.org _uhttps://www.ksp.kit.edu/9783731503590 _70 _zDOAB: download the publication
856	4	0	_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/53685 _70 _zDOAB: description of the publication
999			_c62669 _d62669