Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1998
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dc.contributor.authorSingh J-
dc.contributor.authorDuhan B-
dc.contributor.authorGupta D-
dc.contributor.authorSharma N.-
dc.date.accessioned2021-05-14T11:22:18Z-
dc.date.available2021-05-14T11:22:18Z-
dc.date.issued2020-
dc.identifier.uri10.1109/ICRITO48877.2020.9197840-
dc.identifier.urihttp://hdl.handle.net/123456789/1998-
dc.description.abstractThe idea of cloud computing has reshaped the field of distributed systems, as well as changed how organizations utilizing computing today. Because of the accessibility of limited resources it is exceptionally challenging for cloud service providers to give all the requested resources. Resource management in cloud environment focus upon computing the workload intensive applications that have that have diverse optimization parameters. This study exhibits a complete resource management survey and elaborates broad scientific taxonomy based on the distinct highlights. The scientific taxonomy analyzed most encouraging existing research in resource management and observed monitored values and significant criteria for assessing the viability of several resource management (RM) techniques with their performance evaluation. This paper shows a consecutive study on cloud resource management with broad investigation of particular RM strategies with their evaluation parameters and research issues that should be taken into consideration while suggesting unique RM techniques.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.subjectCloud Resource Managemenen_US
dc.subjectResource Allocationen_US
dc.subjectResource Management Techniquesen_US
dc.subjectResource Scheduling Approaches.en_US
dc.titleCloud Resource Management Optimization: Taxonomy and Research Challengesen_US
dc.typeArticleen_US
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