dc.contributor.author | Khan, Naveed | |
dc.contributor.author | Shrestha, Raju | |
dc.date.accessioned | 2019-07-05T11:43:03Z | |
dc.date.available | 2019-07-05T11:43:03Z | |
dc.date.created | 2019-06-14T11:18:22Z | |
dc.date.issued | 2019 | |
dc.identifier.isbn | 978-989-758-365-0 | |
dc.identifier.uri | http://hdl.handle.net/11250/2603639 | |
dc.description.abstract | With the exponential growth in cloud computing data centers, power consumption due to the use of physical and virtual machines is becoming a challenge. The amount of power consumed by these systems is increasing day by day. In this context, we have done a study on optimizing the power and energy efficiency of physical and virtual machines in a cloud computing environment. By using different tools, the effect of workloads on power consumption and energy efficiency is investigated. This paper presents the findings from our study which provides a good understanding of how different workloads affect power and energy efficiency. Also, the methods and frameworks provided can be used in any cloud environment and of any size in order to investigate and improve energy efficiency. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | SciTePress | nb_NO |
dc.relation.ispartof | CLOSER 2019: Proceedings of the 9th International Conference on Cloud Computing and Services Science | |
dc.title | Optimizing Power and Energy Efficiency in Cloud Computing | nb_NO |
dc.type | Chapter | nb_NO |
dc.description.version | publishedVersion | nb_NO |
dc.source.pagenumber | 380-387 | nb_NO |
dc.identifier.cristin | 1704922 | |
dc.description.localcode | This chapter will not be available due to copyright restrictions (c) 2019 by SciTePress | nb_NO |
cristin.unitcode | 194,63,10,0 | |
cristin.unitname | Institutt for datateknologi og informatikk | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |