TY - GEN
T1 - Site-to-site internet traffic control
AU - Cangialosi, Frank
AU - Narayan, Akshay
AU - Goyal, Prateesh
AU - Mittal, Radhika
AU - Alizadeh, Mohammad
AU - Balakrishnan, Hari
N1 - When multiple bundles (belonging to different sites) compete at the same bottleneck, Bundler’s congestion control would ensure a fair rate allocation across each of these bundles, irrespective of the amount of traffic in them. It, therefore, provides fairness on per-site basis, as opposed to a per-flow basis, making it more robust to popular end-host strategies such as opening multiple connections to increase bandwidth share. 10 CONCLUSION We have described Bundler, a new type of middlebox which uses a novel łinnerž congestion control loop for traffic bundles between two sites to shift the queues from the middle of the network, where it is difficult to unilaterally express traffic control policy, to the site itself, where doing so is tractable. Bundler neither maintains any per-flow state, nor makes any modifications to the packets. We demonstrate, using both emulated network experiments and real Internet paths, that it is possible to shift queues and schedule packets to an extent sufficient to enforce well-known scheduling disciplines. ACKNOWLEDGMENTS We thank Srinivas Narayana, Ahmed Saeed, Rachee Singh, the anonymous EuroSys reviewers, and our shepherd Andreas Haeberlen for their helpful discussions and feedback. This work is supported in part by DARPA contract HR001117C0048 and NSF grants 1526791, 1563826, 2006346, and 1407470.
PY - 2021/4/21
Y1 - 2021/4/21
N2 - Queues allow network operators to control traffic: where queues build, they can enforce scheduling and shaping policies. In the Internet today, however, there is a mismatch between where queues build and where control is most effectively enforced; queues build at bottleneck links that are often not under the control of the data sender. To resolve this mismatch, we propose a new kind of middlebox, called Bundler. Bundler uses a novel inner control loop between a sendbox (in the sender's site) and a receivebox (in the receiver's site) to determine the aggregate rate for the bundle, leaving the end-to-end connections and their control loops intact. Enforcing this sending rate ensures that bottleneck queues that would have built up from the bundle's packets now shift from the bottleneck to the sendbox. This enables the sendbox to exercise control over its traffic by scheduling packets according to any policy necessary to achieve the network operator's higher-level objectives. We have implemented Bundler in Linux and evaluated it with real-world and emulation experiments. We find that Bundler allows the sender-chosen policy to be effective: when configured to implement Stochastic Fairness Queueing (SFQ), it improves median flow completion time (FCT) by between 28% and 97% across various scenarios.
AB - Queues allow network operators to control traffic: where queues build, they can enforce scheduling and shaping policies. In the Internet today, however, there is a mismatch between where queues build and where control is most effectively enforced; queues build at bottleneck links that are often not under the control of the data sender. To resolve this mismatch, we propose a new kind of middlebox, called Bundler. Bundler uses a novel inner control loop between a sendbox (in the sender's site) and a receivebox (in the receiver's site) to determine the aggregate rate for the bundle, leaving the end-to-end connections and their control loops intact. Enforcing this sending rate ensures that bottleneck queues that would have built up from the bundle's packets now shift from the bottleneck to the sendbox. This enables the sendbox to exercise control over its traffic by scheduling packets according to any policy necessary to achieve the network operator's higher-level objectives. We have implemented Bundler in Linux and evaluated it with real-world and emulation experiments. We find that Bundler allows the sender-chosen policy to be effective: when configured to implement Stochastic Fairness Queueing (SFQ), it improves median flow completion time (FCT) by between 28% and 97% across various scenarios.
UR - http://www.scopus.com/inward/record.url?scp=85105311043&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85105311043&partnerID=8YFLogxK
U2 - 10.1145/3447786.3456260
DO - 10.1145/3447786.3456260
M3 - Conference contribution
AN - SCOPUS:85105311043
T3 - EuroSys 2021 - Proceedings of the 16th European Conference on Computer Systems
SP - 574
EP - 589
BT - EuroSys 2021 - Proceedings of the 16th European Conference on Computer Systems
PB - Association for Computing Machinery
T2 - 16th European Conference on Computer Systems, EuroSys 2021
Y2 - 26 April 2021 through 28 April 2021
ER -