The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Rethinking virtual network embedding: substrate support for path splitting and migration
Abstract
Network virtualization is a powerful way to run multiple architectures or experiments simultaneously on a shared infrastructure. However, making efficient use of the underlying resources requires effective techniques for virtual network embedding--mapping each virtual network to specific nodes and links in the substrate network. Since the general embedding problem is computationally intractable, past research restricted the problem space to allow efficient solutions, or focused on designing heuristic algorithms. In this paper, we advocate a different approach: rethinking the design of the substrate network to enable simpler embedding algorithms and more efficient use of resources, without restricting the problem space. In particular, we simplify virtual link embedding by: i) allowing the substrate network to split a virtual link over multiple substrate paths and ii) employing path migration to periodically re-optimize the utilization of the substrate network. We also explore node-mapping algorithms that are customized to common classes of virtual-network topologies. Our simulation experiments show that path splitting, path migration,and customized embedding algorithms enable a substrate network to satisfy a much larger mix of virtual networks
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Cites
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Cited by
Virtual Network Embedding: A Survey
Fischer, A., Botero, J. F., Beck, M. T., de Meer, H., & Hesselbach, X. (2013) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2013.013013.00155 · Cited by 1,244
ViNEYard: Virtual Network Embedding Algorithms With Coordinated Node and Link Mapping
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Data Center Network Virtualization: A Survey
Bari, M. F., Boutaba, R., Esteves, R., Granville, L. Z., Podlesny, M., Rabbani, M. G., Zhang, Q., & Zhani, M. F. (2013) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2012.090512.00043 · Cited by 677
Yan, Z., Ge, J., Wu, Y., Li, L., & Li, T. (2020) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2020.2986662 · Cited by 258
Design and evaluation of learning algorithms for dynamic resource management in virtual networks
Mijumbi, R., Gorricho, J.-L., Serrat, J., Claeys, M., De Turck, F., & Latre, S. (2014) · 2014 IEEE Network Operations and Management Symposium (NOMS) · doi:10.1109/noms.2014.6838258 · Cited by 109
Metadata
- Authors
- Yu, M., Yi, Y., Rexford, J., & Chiang, M.
- Venue
- ACM SIGCOMM Computer Communication Review
- Published
- 2008-03-31
- Volume
- 38
- Issue
- 2
- Pages
- 17-29
- ISSN
- 0146-4833 (ISSN-L)
- OpenAlex
- W2114298221
- Cited by
- 1,244
- References
- 18
- FWCI
- 74.07
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.