The DOI matches its Crossref record.
Inside the Social Network's (Datacenter) Network
Open accessAbstract
Large cloud service providers have invested in increasingly larger datacenters to house the computing infrastructure required to support their services. Accordingly, researchers and industry practitioners alike have focused a great deal of effort designing network fabrics to efficiently interconnect and manage the traffic within these datacenters in performant yet efficient fashions. Unfortunately, datacenter operators are generally reticent to share the actual requirements of their applications, making it challenging to evaluate the practicality of any particular design.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
AuTO: scaling deep reinforcement learning for datacenter-scale automatic traffic optimization
Chen, L., Lingys, J., Chen, K., & Liu, F. (2018) · Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication · doi:10.1145/3230543.3230551 · Cited by 282
PINT: Probabilistic In-band Network Telemetry
Ben Basat, R., Ramanathan, S., Li, Y., Antichi, G., Yu, M., & Mitzenmacher, M. (2020) · Proceedings of the Annual conference of the ACM Special Interest Group on Data Communication on the applications, technologies, architectures, and protocols for computer communication · doi:10.1145/3387514.3405894 · Cited by 268
A Survey on Data Center Networking (DCN): Infrastructure and Operations
Xia, W., Zhao, P., Wen, Y., & Xie, H. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2626784 · Cited by 267
Risk based planning of network changes in evolving data centers
Alipourfard, O., Gao, J., Koenig, J., Harshaw, C., Vahdat, A., & Yu, M. (2019) · Proceedings of the 27th ACM Symposium on Operating Systems Principles · doi:10.1145/3341301.3359664 · Cited by 18
Metadata
- Authors
- Roy, A., Zeng, H., Bagga, J., Porter, G., & Snoeren, A. C.
- Venue
- Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication
- Publisher
- ACM
- Published
- 2015-08-17
- Pages
- 123-137
- OpenAlex
- W1988150362
- Cited by
- 849
- References
- 0
- FWCI
- 53.42
- Type
- conference paper
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Inside the Social Network's (Datacenter) Network. https://app.cochat.ai/papers/10.1145/2785956.2787472
- The paper
- Roy, A., Zeng, H., Bagga, J., Porter, G., & Snoeren, A. C. (2015). Inside the Social Network's (Datacenter) Network. Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication. https://doi.org/10.1145/2785956.2787472
Data sources
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.