Topology discovery can be used to obtain the connectivity and operational status of network devices by discovered interfaces. By performing topology discovery on networks, administrators can better understand and manage networks and improve network reliability and security. However, the large IPv6 address space, sparse address distribution, and unknown address assignment policies make it infeasible to simply and roughly probe the IPv6 network topology. To this end, we design an efficient IPv6 interface-level topology discovery method called TopoMiner. It performs multiple rounds of probing the IPv6 topology with the given set of IPv6 prefixes and locates the high-density interface regions based on the results of each round of topology discovery. TopoMiner then performs prefix expansion and address generation for the high-density interface address regions. At the same time, TopoMiner also uses some of the prefixes that have been probed to regenerate the target addresses. In this way, TopoMiner can dynamically adjust the breadth and depth of topology discovery and thus complete multiple rounds of topology discovery within the packetsending budget. In real-word probing, TopoMiner achieves a$3 \sim 7 \times$enhancement in probing efficiency compared to state-of-the-art topology discovery methods.

We introduce TopoHunter, an efficient IPv6 Internet topology discovery system. The central concept of TopoHunter is to allocate more probing resources to target prefix spaces that yield greater topological benefits, as well as to their surrounding areas. To achieve this, we design a feedback-based target generation module comprised of a Target Prefix Probing Value Forest that maintains the estimated probing values of hierarchical target prefix spaces. Our system has successfully discovered the most extensive and complete IPv6 topology map to date, comprising over 144 million router interfaces and 251 million edges, covering 72.83% of autonomous systems and 43.36% of routing prefixes announced by the BGP system.