Uploaded June 2015 | Updated September 2026, 5 hours ago
This talk was given by undergraduate Ryan Doyle during the 9th Annual Computer Science Undergraduate Research Symposium in 2015. Ryan‘s research was supervised by Dr. Kevin Jeffay.
“Testing the Effectiveness of AQMs at Improving Network Performance”
As use of the Internet and the number of real-time applications that depend on it increases, network performance statistics such as link utilization and average response time become more important. Today, most routers use a basic drop tail style of queueing in which the queue is unmanaged. When the queue is full, every packet arriving at the router is dropped. TCP, the Internet’s dominant transport protocol, has a congestion control mechanism that responds to dropped packets by limiting the rate at which the affected connection sends packets. If many packets from different TCP connections are dropped by a router at the same time, all of those connections will limit their throughput, creating the potential for significant loss in link utilization. In addition to this link utilization problem, drop tail queueing allows for the potential of a buffer to fill and remain full, adding delay to every packet that arrives at the router.
Active queue management algorithms (AQMs) run on routers, replace the standard drop tail method of queueing, and manage the queue before it becomes full. By selectively dropping or marking packets before the router becomes full, AQMs theoretically limit buffer-related delay and increase link utilization by preventing the dropping of packets from many different TCP connections at the same time. In our research, we have constructed and calibrated a network designed to replay actual Internet traffic in a laboratory setting. By implementing different AQMs on the routers in our network, we can test the effectiveness of these algorithms compared to drop tail queuing and will report on the results of these experiments.
Ryan Doyle grew up in New Bern, NC. He spent much of his childhood sailing, but, as an Eagle Scout, also enjoys hiking and camping. Just prior to high school, Ryan taught himself how to program. He worked for OptoSonics, Inc. on photoacoustic angiography of the breast and was published in Medical Physics in 2010. He then attended the North Carolina School of Science and Mathematics before deciding to attend UNC Chapel Hill. Ryan is currently a BS/MS student researching the effects of active queue management algorithms on network performance.
http://cs.unc.edu/academics/undergraduate/symposium/symposium-2015/
This talk was given by undergraduate Ryan Doyle during the 9th Annual Computer Science Undergraduate Research Symposium in 2015. Ryan‘s research was supervised by Dr. Kevin Jeffay.
“Testing the Effectiveness of AQMs at Improving Network Performance”
As use of the Internet and the number of real-time applications that depend on it increases, network performance statistics such as link utilization and average response time become more important. Today, most routers use a basic drop tail style of queueing in which the queue is unmanaged. When the queue is full, every packet arriving at the router is dropped. TCP, the Internet’s dominant transport protocol, has a congestion control mechanism that responds to dropped packets by limiting the rate at which the affected connection sends packets. If many packets from different TCP connections are dropped by a router at the same time, all of those connections will limit their throughput, creating the potential for significant loss in link utilization. In addition to this link utilization problem, drop tail queueing allows for the potential of a buffer to fill and remain full, adding delay to every packet that arrives at the router.
Active queue management algorithms (AQMs) run on routers, replace the standard drop tail method of queueing, and manage the queue before it becomes full. By selectively dropping or marking packets before the router becomes full, AQMs theoretically limit buffer-related delay and increase link utilization by preventing the dropping of packets from many different TCP connections at the same time. In our research, we have constructed and calibrated a network designed to replay actual Internet traffic in a laboratory setting. By implementing different AQMs on the routers in our network, we can test the effectiveness of these algorithms compared to drop tail queuing and will report on the results of these experiments.
Ryan Doyle grew up in New Bern, NC. He spent much of his childhood sailing, but, as an Eagle Scout, also enjoys hiking and camping. Just prior to high school, Ryan taught himself how to program. He worked for OptoSonics, Inc. on photoacoustic angiography of the breast and was published in Medical Physics in 2010. He then attended the North Carolina School of Science and Mathematics before deciding to attend UNC Chapel Hill. Ryan is currently a BS/MS student researching the effects of active queue management algorithms on network performance.
http://cs.unc.edu/academics/undergraduate/symposium/symposium-2015/
