New Decrease-and-Conquer Strategies for the Dynamic Genetic Algorithm for Server Consolidation

Author:

Sonklin Chanipa,Tang Maolin,Tian Yu-Chu

Publisher

Springer International Publishing

Reference8 articles.

1. Dong, J., Jin, X., Wang, H., Li, Y., Zhang, P., Cheng, S.: Energy-saving virtual machine placement in cloud data centers. In: 2013 13th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 618–624, May 2013

2. Sarker, T.K., Tang, M.: Performance-driven live migration of multiple virtual machines in datacenters. In: IEEE International Conference on Granular Computing, pp. 253–258 (2013)

3. Sonklin, C., Tang, M., Tian, Y.C.: A decrease-and-conquer genetic algorithm for energy efficient virtual machine placement in data centers. In: IEEE International Conference on Industrial Informatics. IEEE Press, July 2017, in press

4. Tang, M., Pan, S.: A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers. Neural Process. Lett. 41(2), 211–221 (2015)

5. Whitney, J., Delforge, P.: Data center efficiency assessment-scaling up energy efficiency across the data center industry: evaluating key drivers and barriers. NRDC and Anthesis, Rep. IP: 14–08 (2014)

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