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A self-clocked fair queueing scheme for broadband applications
Abstract
An efficient fair queueing scheme which is feasible for broadband implementation is proposed and its performance is analyzed. The author defines fairness in a self-contained manner, eliminating the need for the hypothetical fluid-flow reference system used in the present state of art and thereby removing the associated computational complexity. The scheme is based on the adoption of an internally generated virtual time as the index of work progress, hence the name self-clocked fair queueing. The author proves that the scheme possesses the desired fairness property and is nearly optimal, in the sense that the maximum permissible disparity among the normalized services offered to the backlogged sessions is never more than two times the corresponding figure in any packet-based queueing system.>
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Cited by
Efficient fair queuing using deficit round-robin
Shreedhar, M., & Varghese, G. (1996) · IEEE/ACM Transactions on Networking · doi:10.1109/90.502236 · Cited by 1,399
Chen, S., & Nahrstedt, K. (1998) · IEEE Network · doi:10.1109/65.752646 · Cited by 874
Metadata
- Authors
- Golestani, S. J.
- Venue
- Proceedings of INFOCOM '94 Conference on Computer Communications
- Publisher
- IEEE Comput. Soc. Press
- Published
- 2002-12-17
- Pages
- 636-646
- OpenAlex
- W2139475785
- Cited by
- 1,100
- References
- 0
- FWCI
- 88.04
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A self-clocked fair queueing scheme for broadband applications. https://app.cochat.ai/papers/10.1109/infcom.1994.337677
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- Golestani, S. J. (2002). A self-clocked fair queueing scheme for broadband applications. Proceedings of INFOCOM '94 Conference on Computer Communications. https://doi.org/10.1109/infcom.1994.337677
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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.
