植物群
发表于 2025-3-30 08:23:11
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牲畜栏
发表于 2025-3-30 13:33:05
Fu Guo,Long Ren,Zhenke He,Haiying Wangthis framework in order to get the predicted VM energy consumption. Compared with actual results obtained in a real Cloud testbed, the predicted results show that this energy-aware prediction framework can get up to 2.58 Mean Percentage Error (MPE) for the VM workload prediction, and up to −4.47 MPE
exigent
发表于 2025-3-30 17:37:31
Chi-Hsien Hsu,Chih-Long Lin,Rungtai Lind such that enforcing GMF provides incentives to users to configure virtual resources of their VMs in-line with the VMs’ subsequent resource PR utilization allowing cloud providers to schedule these VMs more efficiently. Finally, this work here proves that GMF provides for the same desirable charact
遣返回国
发表于 2025-3-30 23:32:29
Mei-Hsien Huang,Wanyu Houng,Rungtai Linthis framework in order to get the predicted VM energy consumption. Compared with actual results obtained in a real Cloud testbed, the predicted results show that this energy-aware prediction framework can get up to 2.58 Mean Percentage Error (MPE) for the VM workload prediction, and up to −4.47 MPE
补充
发表于 2025-3-31 03:36:16
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Jacket
发表于 2025-3-31 07:36:30
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tendinitis
发表于 2025-3-31 11:18:10
Luciana Cardoso de Castro Salgado,Clarisse Sieckenius de Souza,Carla Faria Leitão the status quo. With throughputs surpassing 100 Gb/s in 2021, even large tasks can be migrated within a few seconds. In light of these improvements, we believe it is time to rethink the application of resource overcommitment and live migration to improve data center resource utilization. Based on r
ineptitude
发表于 2025-3-31 14:58:44
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Entreaty
发表于 2025-3-31 19:20:37
Mo-Li Yeh,Po-Hsien Lin the status quo. With throughputs surpassing 100 Gb/s in 2021, even large tasks can be migrated within a few seconds. In light of these improvements, we believe it is time to rethink the application of resource overcommitment and live migration to improve data center resource utilization. Based on r
MOAN
发表于 2025-4-1 01:37:36
stances of the applications executed in system. This result is achieve without violating the services’ QoE, expressed in terms of latency. Experimental evaluations through simulation conducted with PureEdgeSim demonstrate the effectiveness of the approach.