Implementing Scalable, Network-Aware Virtual Machine Migration for Cloud Data Centers (bibtex)
by Fung Po Tso, Gregg Hamilton, Konstantinos Oikonomou, Dimitrios Pezaros
Abstract:
Virtualization has been key to the success of Cloud Computing through the on-demand allocation of shared hardware resources to Virtual MAChines (VM)s. However, the network-agnostic placement of VMs over the underlying network topology can itself be a factor of performance degradation by causing congestion at the core layers of the infrastructure where bandwidth is heavily oversubscribed. In this paper, we design and implement S-CORE, a scalable live VM migration scheme to dynamically reallocate VMs to servers while minimizing the overall communication footprint of active traffic flows. We evaluate S-CORE over diverse aggregate load and coordination policies. Our results show that it can achieve up to a 87\% communication cost reduction with a limited number of migration rounds, and can be easily accommodated within commodity hardware and hypervisor architectures. The associated memory, CPU, and network overhead are also minimum under typical Cloud Data Center workloads.
Reference:
Fung Po Tso, Gregg Hamilton, Konstantinos Oikonomou, Dimitrios Pezaros, "Implementing Scalable, Network-Aware Virtual Machine Migration for Cloud Data Centers", In 2013 IEEE Sixth International Conference on Cloud Computing, pp. 557-564, 2013.
Bibtex Entry:
@inproceedings{tso2013implementing,
	Abstract = {Virtualization has been key to the success of Cloud Computing through the on-demand allocation of shared hardware resources to Virtual MAChines (VM)s. However, the network-agnostic placement of VMs over the underlying network topology can itself be a factor of performance degradation by causing congestion at the core layers of the infrastructure where bandwidth is heavily oversubscribed. In this paper, we design and implement S-CORE, a scalable live VM migration scheme to dynamically reallocate VMs to servers while minimizing the overall communication footprint of active traffic flows. We evaluate S-CORE over diverse aggregate load and coordination policies. Our results show that it can achieve up to a 87\% communication cost reduction with a limited number of migration rounds, and can be easily accommodated within commodity hardware and hypervisor architectures. The associated memory, CPU, and network overhead are also minimum under typical Cloud Data Center workloads.},
	Author = {Tso, Fung Po and Hamilton, Gregg and Oikonomou, Konstantinos and Pezaros, Dimitrios},
	Booktitle = {2013 IEEE Sixth International Conference on Cloud Computing},
	Doi = {10.1109/CLOUD.2013.82},
	Issn = {2159-6182},
	Keywords = {own, pezaros, refereed},
	Month = {June},
	Pages = {557--564},
	Title = {{{Implementing Scalable, Network-Aware Virtual Machine Migration for Cloud Data Centers}}},
	Venue = {Santa Clara, USA},
	Year = {2013},
	Bdsk-Url-1 = {https://doi.org/10.1109/CLOUD.2013.82}}
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