Congestion avoidance and control
SIGCOMM '88 Symposium proceedings on Communications architectures and protocols
A control-theoretic approach to flow control
SIGCOMM '91 Proceedings of the conference on Communications architecture & protocols
Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
Measuring bottleneck link speed in packet-switched networks
Performance Evaluation
End-to-end Internet packet dynamics
SIGCOMM '97 Proceedings of the ACM SIGCOMM '97 conference on Applications, technologies, architectures, and protocols for computer communication
Using pathchar to estimate Internet link characteristics
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Detecting shared congestion of flows via end-to-end measurement
Proceedings of the 2000 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Measuring link bandwidths using a deterministic model of packet delay
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
On the constancy of internet path properties
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Multicast-based inference of network-internal delay distributions
IEEE/ACM Transactions on Networking (TON)
Robust identification of shared losses using end-to-end unicast probes
ICNP '00 Proceedings of the 2000 International Conference on Network Protocols
Passive network tomography using EM algorithms
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Multicast-based inference of network-internal loss characteristics
IEEE Transactions on Information Theory
Multicast topology inference from measured end-to-end loss
IEEE Transactions on Information Theory
An architecture for large scale Internet measurement
IEEE Communications Magazine
The use of end-to-end multicast measurements for characterizing internal network behavior
IEEE Communications Magazine
Multicast-based loss inference with missing data
IEEE Journal on Selected Areas in Communications
IP network topology discovery using SNMP
ICOIN'09 Proceedings of the 23rd international conference on Information Networking
Efficient and dynamic routing topology inference from end-to-end measurements
IEEE/ACM Transactions on Networking (TON)
Optimal probing for unicast network delay tomography
INFOCOM'10 Proceedings of the 29th conference on Information communications
Toward the practical use of network tomography for internet topology discovery
INFOCOM'10 Proceedings of the 29th conference on Information communications
Measurement of loss pairs in network paths
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Network link tomography and compressive sensing
Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Network link tomography and compressive sensing
ACM SIGMETRICS Performance Evaluation Review - Performance evaluation review
Efficient network tomography for internet topology discovery
IEEE/ACM Transactions on Networking (TON)
| Hi-index | 0.00 |
In this paper, we explore the use of end-to-end unicast traffic as measurement probes to infer link-level loss rates. We leverage off of earlier work that produced efficient estimates for link-level loss rates based on end-to-end multicast traffic measurements. We design experiments based on the notion of transmitting stripes of packets (with no delay between transmission of successive packets within a stripe) to two or more receivers. The purpose of these stripes is to ensure that the correlation in receiver observations matches as closely as possible what would have been observed if a multicast probe followed the same path to the receivers. Measurements provide good evidence that a packet pair to distinct receivers introduces considerable correlation which can be further increased by simply considering longer stripes. Using an M/M/1/K model for a link, we theoretically confirm this benefit for stripes. We also use simulation to explore how well these stripes translate into accurate link-level loss estimates. We observe good accuracy with packet pairs, with a typical error of about 1%, which significantly decreases as stripe length is increased.