Asymptotic Analysis in Cloud Resource Allocation: Scalability of Virtual Machines, Scheduling Complexity, and Auto-Scaling Mechanisms

Authors

  • Gokul Chandra Purnachandra Reddy

Keywords:

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Abstract

This paper presents a comprehensive analysis of dynamic scaling and resource management in cloud computing environments. It explores the asymptotic behavior of virtual machine (VM) and container provisioning, the computational complexity of resource scheduling strategies, and the performance of auto-scaling mechanisms under varying workload conditions.

References

M. Mao and M. Humphrey, "A Performance Study on the VM Startup Time in the Cloud," in 2012 IEEE Fifth International Conference on Cloud Computing, Honolulu, HI, USA, 2012, pp. 423–430.

A. Verma, P. Ahuja, and A. Neogi, "pMapper: Power and Migration Cost Aware Application Placement in Virtualized Systems," in Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware, Leuven, Belgium, 2008, pp. 243–264.

N. Bobroff, A. Kochut, and K. Beaty, "Dynamic Placement of Virtual Machines for Managing SLA Violations," in Proceedings of the 10th IFIP/IEEE International Symposium on Integrated Network Management, Munich, Germany, 2007, pp. 119–128.

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Published

2017-12-01

How to Cite

Gokul Chandra Purnachandra Reddy. (2017). Asymptotic Analysis in Cloud Resource Allocation: Scalability of Virtual Machines, Scheduling Complexity, and Auto-Scaling Mechanisms . Journal of Computational Analysis and Applications (JoCAAA), 27(7), 23–43. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/1951

Issue

Vol. 27 No. 7 (2019): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.