2020 15th Iberian Conference on Information Systems and Technologies (CISTI) 2020
DOI: 10.23919/cisti49556.2020.9141159
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A Hybrid Automatic Elasticity Solution for the IaaS Layer based on Dynamic Thresholds and Time Series

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Cited by 2 publications
(5 citation statements)
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“…Zhang et al [14] designed a thresholdbased procedure to scale containers in a cloud platform and then measured the elasticity of their algorithm. In a hybrid approach, Gervásio et al [15] combined an ensemble of prediction models with a dynamic threshold algorithm to scale virtual machines in an AWS cloud. Ullah et al [16] used genetic algorithm and artificial neural networks to predict CPU usage in a cloud and then used a thresholdbased rule.…”
Section: Related Workmentioning
confidence: 99%
See 2 more Smart Citations
“…Zhang et al [14] designed a thresholdbased procedure to scale containers in a cloud platform and then measured the elasticity of their algorithm. In a hybrid approach, Gervásio et al [15] combined an ensemble of prediction models with a dynamic threshold algorithm to scale virtual machines in an AWS cloud. Ullah et al [16] used genetic algorithm and artificial neural networks to predict CPU usage in a cloud and then used a thresholdbased rule.…”
Section: Related Workmentioning
confidence: 99%
“…From the related literature review, it is observed that scaling algorithms reported in most of the literature works so far control the number of VM, VNF, container instances with the use of some thresholds [14], [15], [18], [30]- [33]. However, to our best knowledge, no existing work on the application of artificial intelligence methods for the resource management of UPF instances.…”
Section: Related Workmentioning
confidence: 99%
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“…Casalicchio [19] carried out measurements about the scaling of Kubernetes Pods and argued that the scaling should consider the Quality of Service aspects. Gervásio et al [20] in their hybrid autoscaling proposal, combined a self-adaptive prediction and reactive approach for optimal configuration of the threshold values for scaling operations. Ullah et al [21] presented the combination of predictive and reactive approach where Cartesian genetic programming based neural network is used for resource estimation and a rule-based scaling.…”
Section: Related Workmentioning
confidence: 99%
“…From the related literature review, it is observed that scaling algorithms reported in most of the literature works so far control the number of VM, VNF, container instances with the use of some thresholds [14]- [20]. However, to our best knowledge, no existing work on the queueing analysis for the scaling of 5G UPF instances based on threshold algorithms has been presented.…”
Section: Related Workmentioning
confidence: 99%