The Packet-Scale Congestion Control is a new paradigm that allows end-to-end transport protocols to scale to ultra-high speed networks.  While most existing protocols can attain a single-stream throughput of no more than a few Gigabits-per-second, this paradigm promises to scale to up to Terabit-and-higher speeds.

It does so by shedding the legacy framework of RTT-scale operation that is adopted by most existing congestion-control protocols — this allows protocols based on the packet-scale paradigm to operate at much finer timescales than are currently possible. The paradigm itself relies on two main ideas: (i) fine-scale probing that creates finely-controlled inter-packet spacing at the sender and observes changes in these at the receiver to estimate the current available bandwidth in the network, and (ii) probing-without-overloading, which exploits the fine-scale of probing to probe for a wide-range of rates within an RTT, without causing persistent queuing at bottleneck links.  The paradigm also helps truly achieve RTT fairness and friendliness to conventional TCP traffic — two goals that have so far remained allusive to high-speed transport protocols.

The paradigm, however, brings up new challenges that are not dominant ones for RTT-scale protocols. These include:

  • The sensitivity of the paradigm to “noise” in the end-to-end delays experienced by packets.
  • The implementation of fine-scaled inter-packet spacing in current end-systems.
  • The stability, sensitivity, and fairness of the paradigm under stressful traffic conditions.

These are the subject of our current research in this project.

 


Check out this recent interview on our collaboration with RENCI on using the BEN network.

 

Benefits of BEN from RENCI on Vimeo.


 

This research is supported in part by:

NSF CISE

NSF OCI

UNC CAS

This material is based upon work partially supported by the National Science Foundation under Grant No. OCI-1127413, Grant No. CNS-1018596, and CAREER Award No. CNS-0347814, and by a UNC Associate Professor Award. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.