On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Delayed Internet routing convergence
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
Avoiding traceroute anomalies with Paris traceroute
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Mapping and visualizing the internet
ATEC '00 Proceedings of the annual conference on USENIX Annual Technical Conference
SSS '09 Proceedings of the 11th International Symposium on Stabilization, Safety, and Security of Distributed Systems
Improving content delivery using provider-aided distance information
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
On the hardness of topology inference
ICDCN'11 Proceedings of the 12th international conference on Distributed computing and networking
Topology discovery of sparse random graphs with few participants
Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
The weak network tracing problem
ICDCN'10 Proceedings of the 11th international conference on Distributed computing and networking
Network Topology Inference Based on End-to-End Measurements
IEEE Journal on Selected Areas in Communications
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Traceroute measurements are one of the main instruments to shed light onto the structure and properties of today's complex networks such as the Internet. This paper studies the feasibility and infeasibility of inferring the network topology given traceroute data from a worst-case perspective, i.e., without any probabilistic assumptions on, e.g., the nodes' degree distribution. We attend to a scenario where some of the routers are anonymous, and propose two fundamental axioms that model two basic assumptions on the traceroute data: (1) each trace corresponds to a real path in the network, and (2) the routing paths are at most a factor 1/α off the shortest paths, for some parameter α ε (0, 1]. In contrast to existing literature that focuses on the cardinality of the set of (often only minimal) inferrable topologies, we argue that a large number of possible topologies alone is often unproblematic, as long as the networks have a similar structure. We hence seek to characterize the set of topologies inferred with our axioms. We introduce the notion of star graphs whose colorings capture the differences among inferred topologies; it also allows us to construct inferred topologies explicitly. We find that in general, inferrable topologies can differ significantly in many important aspects, such as the nodes' distances or the number of triangles. These negative results are complemented by a discussion of a scenario where the trace set is best possible, i.e., "complete". It turns out that while some properties such as the node degrees are still hard to measure, a complete trace set can help to determine global properties such as the connectivity.