Abstract
We are developing an advanced IaaS (Infrastructure-as-a-Service) datacenter management system that dynamically minimizes running physical servers depending on resource utilization. The management system periodically monitors the loading of a datacenter, and dynamically repacks virtual machines (VMs) into optimal physical servers. Live migration of VMs and the standby mode of physical servers are automatically orchestrated by a genetic algorithm (GA) engine. A preliminary experiment showed that our first prototype system correctly worked for a proof-of-concept datacenter.
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References
Hirofuchi, T., Nakada, H., Itoh, S., Sekiguchi, S.: Enabling instantaneous relocation of virtual machines with a lightweight vmm extension. In: Proceedings of the 10th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2010), IEEE Computer Society, Los Alamitos (2010)
Nakada, H., Hirofuchi, T., Ogawa, H., Itoh, S.: Toward virtual machine packing optimization based on genetic algorithm. In: Omatu, S., Rocha, M.P., Bravo, J., Fernández, F., Corchado, E., Bustillo, A., Corchado, J.M. (eds.) IWANN 2009. LNCS, vol. 5518, pp. 651–654. Springer, Heidelberg (2009)
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Hirofuchi, T., Nakada, H., Ogawa, H., Itoh, S., Sekiguchi, S. (2010). Eliminating Datacenter Idle Power with Dynamic and Intelligent VM Relocation. In: de Leon F. de Carvalho, A.P., RodrÃguez-González, S., De Paz Santana, J.F., RodrÃguez, J.M.C. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 79. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14883-5_82
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DOI: https://doi.org/10.1007/978-3-642-14883-5_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14882-8
Online ISBN: 978-3-642-14883-5
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