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Cited by 362

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Joint VM placement and routing for data center traffic engineering

Jiang, Joe Wenjie, Lan, Tian, Ha, Sangtae, Chen, Minghua, Chiang, Mung·2012·2012 Proceedings IEEE INFOCOM

Abstract

Today's data centers need efficient traffic management to improve resource utilization in their networks. In this work, we study a joint tenant (e.g., server or virtual machine) placement and routing problem to minimize traffic costs. These two complementary degrees of freedom—placement and routing—are mutually-dependent, however, are often optimized separately in today's data centers. Leveraging and expanding the technique of Markov approximation, we propose an efficient online algorithm in a dynamic environment under changing traffic loads. The algorithm requires a very small number of virtual machine migrations and is easy to implement in practice. Performance evaluation that employs the real data center traffic traces under a spectrum of elephant and mice flows, demonstrates a consistent and significant improvement over the benchmark achieved by common heuristics.

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Metadata

Authors
Jiang, J. W., Lan, T., Ha, S., Chen, M., & Chiang, M.
Venue
2012 Proceedings IEEE INFOCOM
Publisher
IEEE
Published
2012-03
Pages
2876-2880
OpenAlex
W2039612281
Cited by
362
References
9
FWCI
33.86
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Joint VM placement and routing for data center traffic engineering. https://app.cochat.ai/papers/10.1109/infcom.2012.6195719
The paper
Jiang, J. W., Lan, T., Ha, S., Chen, M., & Chiang, M. (2012). Joint VM placement and routing for data center traffic engineering. 2012 Proceedings IEEE INFOCOM. https://doi.org/10.1109/infcom.2012.6195719

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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.