TY - GEN
T1 - Waypoint-based Topology Inference
AU - Lin, Yilei
AU - He, Ting
AU - Wang, Shiqiang
AU - Chan, Kevin
N1 - Funding Information:
This research was partly sponsored by the U.S. Army Research Laboratory and the U.K. Ministry of Defence under Agreement Number W911NF-16-3-0001
Funding Information:
This research was partly sponsored by the U.S. Army Research Laboratory and the U.K. Ministry of Defence under Agreement Number W911NF-16-3-0001. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies of the U.S. Army Research Laboratory, the U.S. Government, the U.K. Ministry of Defence or the U.K. Government. The U.S. and U.K. Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - Traditional network topology inference aims at reconstructing the routing trees rooted at each probing source from end-to-end measurements. However, due to emerging technologies such as network function virtualization, software defined networking, and segment routing, many modern networks are capable of supporting generalized forwarding that can create complex routing topologies different from routing trees. In this work, we take a first step towards closing this gap by proposing methods to infer the routing topology (referred to as 1-1-N topology) from a single source to multiple destinations, where routes may be required to traverse a given waypoint. We first thoroughly study the special case of 1-1-2 topologies, showing that even this seemingly simple case is highly nontrivial with 36 possibilities. We then demonstrate how the solution to the special case can be used as building blocks to infer 1-1-N topologies. The inferred topology is proved to be equivalent to the ground truth up to splitting/combining edges in the same category.
AB - Traditional network topology inference aims at reconstructing the routing trees rooted at each probing source from end-to-end measurements. However, due to emerging technologies such as network function virtualization, software defined networking, and segment routing, many modern networks are capable of supporting generalized forwarding that can create complex routing topologies different from routing trees. In this work, we take a first step towards closing this gap by proposing methods to infer the routing topology (referred to as 1-1-N topology) from a single source to multiple destinations, where routes may be required to traverse a given waypoint. We first thoroughly study the special case of 1-1-2 topologies, showing that even this seemingly simple case is highly nontrivial with 36 possibilities. We then demonstrate how the solution to the special case can be used as building blocks to infer 1-1-N topologies. The inferred topology is proved to be equivalent to the ground truth up to splitting/combining edges in the same category.
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U2 - 10.1109/ICC40277.2020.9149348
DO - 10.1109/ICC40277.2020.9149348
M3 - Conference contribution
AN - SCOPUS:85089428666
T3 - IEEE International Conference on Communications
BT - 2020 IEEE International Conference on Communications, ICC 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Communications, ICC 2020
Y2 - 7 June 2020 through 11 June 2020
ER -