Performance and Energy-Based Cost Prediction of Virtual Machines Auto-Scaling in Clouds

@article{Aldossary2018PerformanceAE,
  title={Performance and Energy-Based Cost Prediction of Virtual Machines Auto-Scaling in Clouds},
  author={Mohammad Aldossary and Karim Djemame},
  journal={2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)},
  year={2018},
  pages={502-509}
}
Virtual Machines (VMs) auto-scaling is an important technique to provision additional resource capacity in a Cloud environment. It allows the VMs to dynamically increase or decrease the amount of resources as needed in order to meet Quality of Service (QoS) requirements. However, the auto-scaling mechanism can be time-consuming to initiate (e.g. in the order of a minute), which is unacceptable for VMs that need to scale up/out during the computation, besides additional costs due to the increase… CONTINUE READING

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Key Quantitative Results

  • A series of experiments conducted on a Cloud testbed show that this framework is capable of predicting the auto-scaling workload, power consumption and total cost for heterogeneous VMs, with a cost-saving of up to 25% for the predicted total cost of VM self-configuration as compared to the current approaches in literature.

Citations

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Energy-based Cost Model of Virtual Machines in a Cloud Environment

  • 2018 Fifth International Symposium on Innovation in Information and Communication Technology (ISIICT)
  • 2018
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CITES BACKGROUND

References

Publications referenced by this paper.
SHOWING 1-10 OF 15 REFERENCES

PaaS-IaaS Inter-Layer Adaptation in an Energy-Aware Cloud Environment

  • IEEE Transactions on Sustainable Computing
  • 2017
VIEW 1 EXCERPT

An Auto-Scaling Framework for Controlling Enterprise Resources on Clouds

  • 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
  • 2015
VIEW 1 EXCERPT

Evaluating Auto-scaling Strategies for Cloud Computing Environments

  • 2014 IEEE 22nd International Symposium on Modelling, Analysis & Simulation of Computer and Telecommunication Systems
  • 2014
VIEW 1 EXCERPT

Amazon EC2 Service Level Agreement

AmazonEC2
  • 2013. [Online]. Available: https://aws.amazon.com/ec2/sla/. [Accessed: 01-Oct-2017].
  • 2013
VIEW 1 EXCERPT

Lightweight Resource Scaling for Cloud Applications

  • 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
  • 2012
VIEW 1 EXCERPT

RPPS: A Novel Resource Prediction and Provisioning Scheme in Cloud Data Center

  • 2012 IEEE Ninth International Conference on Services Computing
  • 2012
VIEW 1 EXCERPT

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