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handle: 2117/19310
Cloud computing provides an efficient and flexible means for various services to meet the diverse and escalating needs of IT end-users. It offers novel functionalities including the utilization of remote services in addition to the virtualization technology. The latter feature offers an efficient method to harness the cloud power by fragmenting a cloud physical host in small manageable virtual portions. As a norm, the virtualized parts are generated by the cloud provider administrator through the hyper visor software based on a generic need for various services. However, several obstacles arise from this generalized and static approach. In this paper, we study and propose a model for instantiating dynamically virtual machines in relation to the current job characteristics. Following, we simulate a virtualized cloud environment in order to evaluate the model's dynamic-ness by measuring the correlation of virtual machines to hosts for certain job variations. This will allow us to compute the expected average execution time of various virtual machines instantiations per job length. Peer Reviewed
Static and dynamic virtual machine scheduling, Computació en núvol, Virtualization, Cloud computing, Cloud, Virtual machine instantiation, Àrees temàtiques de la UPC::Informàtica::Programació, :Informàtica::Programació [Àrees temàtiques de la UPC]
Static and dynamic virtual machine scheduling, Computació en núvol, Virtualization, Cloud computing, Cloud, Virtual machine instantiation, Àrees temàtiques de la UPC::Informàtica::Programació, :Informàtica::Programació [Àrees temàtiques de la UPC]
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 16 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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