Virtual machine placement quality estimation in cloud infrastructures using integer linear programming
Author:
Funder
Celtic-Plus European project
Publisher
Springer Science and Business Media LLC
Subject
Safety, Risk, Reliability and Quality,Software
Link
http://link.springer.com/content/pdf/10.1007/s11219-018-9420-z.pdf
Reference27 articles.
1. Babu, K.R.R., & Samuel, P. (2014). Virtual machine placement for improved quality in IaaS cloud. In 2014 4th international conference on advances in computing and communications (pp. 190–194). https://doi.org/10.1109/ICACC.2014.53 .
2. Beloglazov, A., & Buyya, R. (2012). Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers. Concurrency and Computation: Practice and Experience, 24(13), 1397–1420. https://doi.org/10.1002/cpe.1867 .
3. Bonde, D. (2010). Techniques for virtual machine placement in clouds. Master’s thesis, Indian Institute of Computer Science and Engineering.
4. Calheiros, R.N., Ranjan, R., Beloglazov, A., De Rose, C.A.F., Buyya, R. (2011). Cloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and Experience, 41(1), 23–50. https://doi.org/10.1002/spe.995 .
5. Chowdhury, M.R., Mahmud, M.R., Rahman, R.M. (2015). Implementation and performance analysis of various vm placement strategies in cloudsim. Journal of Cloud Computing, 4(1), 20. https://doi.org/10.1186/s13677-015-0045-5 .
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