TY - GEN
T1 - Stochastic forecasts achieve high throughput and low delay over cellular networks
AU - Winstein, Keith
AU - Sivaraman, Anirudh
AU - Balakrishnan, Hari
N1 - Funding Information:
We thank Shuo Deng, Jonathan Perry, Katrina LaCurts, Andrew McGregor, Tim Shepard, Dave T?ht, Michael Welzl, Hannes Tschofenig, and the anonymous reviewers for helpful discussion and feedback. This work was supported in part by NSF grant 1040072. KW was supported by the Claude E. Shannon Research Assistantship. We thank the members of the MIT Center for Wireless Networks and Mobile Computing, including Amazon.com, Cisco, Google, Intel, Mediatek, Microsoft, ST Microelectronics, and Telefonica, for their support.
Funding Information:
We thank Shuo Deng, Jonathan Perry, Katrina LaCurts, Andrew McGregor, Tim Shepard, Dave Täht, Michael Welzl, Hannes Tschofenig, and the anonymous reviewers for helpful discussion and feedback. This work was supported in part by NSF grant 1040072. KW was supported by the Claude E. Shannon Research Assistantship. We thank the members of the MIT Center for Wireless Networks and Mobile Computing, including Amazon.com, Cisco, Google, Intel, Mediatek, Microsoft, ST Microelectronics, and Telefonica, for their support.
Publisher Copyright:
© Proceedings of the 10th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2013. All rights reserved.
PY - 2013
Y1 - 2013
N2 - Sprout is an end-to-end transport protocol for interactive applications that desire high throughput and low delay. Sprout works well over cellular wireless networks, where link speeds change dramatically with time, and current protocols build up multi-second queues in network gateways. Sprout does not use TCP-style reactive congestion control; instead the receiver observes the packet arrival times to infer the uncertain dynamics of the network path. This inference is used to forecast how many bytes may be sent by the sender, while bounding the risk that packets will be delayed inside the network for too long. In evaluations on traces from four commercial LTE and 3G networks, Sprout, compared with Skype, reduced self-inflicted end-to-end delay by a factor of 7.9 and achieved 2.2× the transmitted bit rate on average. Compared with Google's Hangout, Sprout reduced delay by a factor of 7.2 while achieving 4.4× the bit rate, and compared with Apple's Facetime, Sprout reduced delay by a factor of 8.7 with 1.9× the bit rate. Although it is end-to-end, Sprout matched or outperformed TCP Cubic running over the CoDel active queue management algorithm, which requires changes to cellular carrier equipment to deploy. We also tested Sprout as a tunnel to carry competing interactive and bulk traffic (Skype and TCP Cubic), and found that Sprout was able to isolate client application flows from one another.
AB - Sprout is an end-to-end transport protocol for interactive applications that desire high throughput and low delay. Sprout works well over cellular wireless networks, where link speeds change dramatically with time, and current protocols build up multi-second queues in network gateways. Sprout does not use TCP-style reactive congestion control; instead the receiver observes the packet arrival times to infer the uncertain dynamics of the network path. This inference is used to forecast how many bytes may be sent by the sender, while bounding the risk that packets will be delayed inside the network for too long. In evaluations on traces from four commercial LTE and 3G networks, Sprout, compared with Skype, reduced self-inflicted end-to-end delay by a factor of 7.9 and achieved 2.2× the transmitted bit rate on average. Compared with Google's Hangout, Sprout reduced delay by a factor of 7.2 while achieving 4.4× the bit rate, and compared with Apple's Facetime, Sprout reduced delay by a factor of 8.7 with 1.9× the bit rate. Although it is end-to-end, Sprout matched or outperformed TCP Cubic running over the CoDel active queue management algorithm, which requires changes to cellular carrier equipment to deploy. We also tested Sprout as a tunnel to carry competing interactive and bulk traffic (Skype and TCP Cubic), and found that Sprout was able to isolate client application flows from one another.
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M3 - Conference contribution
T3 - Proceedings of the 10th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2013
SP - 459
EP - 471
BT - Proceedings of the 10th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2013
PB - USENIX Association
T2 - 10th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2013
Y2 - 2 April 2013 through 5 April 2013
ER -