APA
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Tangenes, T., Hayes, D. A., Petlund, A., & Ros, D. (2017). Evaluating CAIA delay gradient as a candidate for deadline-aware less-than-best-effort transport. In Proceedings of the 2017 IFIP Networking Conference (IFIP Networking) and Workshops. https://doi.org/10.23919/IFIPNetworking.2017.8264882
Chicago/Turabian
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Tangenes, T., D. A. Hayes, A. Petlund, and D. Ros. “Evaluating CAIA Delay Gradient as a Candidate for Deadline-Aware Less-than-Best-Effort Transport.” In Proceedings of the 2017 IFIP Networking Conference (IFIP Networking) and Workshops, 2017.
MLA
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Tangenes, T., et al. “Evaluating CAIA Delay Gradient as a Candidate for Deadline-Aware Less-than-Best-Effort Transport.” Proceedings of the 2017 IFIP Networking Conference (IFIP Networking) and Workshops, 2017, doi:10.23919/IFIPNetworking.2017.8264882.
BibTeX Click to copy
@inproceedings{t2017a,
title = {Evaluating CAIA delay gradient as a candidate for deadline-aware less-than-best-effort transport},
year = {2017},
doi = {10.23919/IFIPNetworking.2017.8264882},
author = {Tangenes, T. and Hayes, D. A. and Petlund, A. and Ros, D.},
booktitle = {Proceedings of the 2017 IFIP Networking Conference (IFIP Networking) and Workshops}
}
Less-than-best-effort (LBE) congestion control offers a low-priority service for applications tolerant to high latency and low throughput, like peer-to-peer file transfers or automatic software updates. There are, however, situations where it would be beneficial for the application to specify a soft deadline for task completion. Examples of such situations could be completion of backup tasks or synchronisation between CDN data centres. Since network conditions change over time, a deadline-aware LBE (DA- LBE) congestion control would need the ability to dynamically adapt how aggressively it competes for capacity to meet the soft deadline, trading low-priority behaviour for timeliness. One candidate that shows promise as a LBE congestion control is CAIA Delay Gradient (CDG). CDG uses changes in measured end-to-end delay to control the congestion window. CDG has several parameters that might help tune its “aggressiveness” in a way that might help achieve the goal of DA-LBE congestion control. We have evaluated CDG in order to establish how it can be tuned to exhibit different degrees of LBE behaviour under varying network conditions. Our results show that it is possible to control CDG to vary its aggressiveness in a consistent way, making it a prime candidate to implement a DA-LBE congestion control system.
