Abstract
To enable efficient resource provisioning in HaaS (Hardware as a Service) cloud systems, virtual machine packing, which migrate virtual machines to minimize running real node, is essential. The virtual machine packing problem is a multi-objective optimization problem with several parameters and weights on parameters change dynamically subject to cloud provider preference. We propose to employ Genetic Algorithm (GA) method, that is one of the meta-heuristics. We implemented a prototype Virtual Machine packing optimization mechanism on Grivon, which is a virtual cluster management system we have been developing. The preliminary evaluation implied the GA method is promising for the problem. © 2009 Springer Berlin Heidelberg.
Cite
CITATION STYLE
Nakada, H., Hirofuchi, T., Ogawa, H., & Itoh, S. (2009). Toward virtual machine packing optimization based on genetic algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5518 LNCS, pp. 651–654). https://doi.org/10.1007/978-3-642-02481-8_96
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