Discovery of Network Properties with All-Shortest-Paths Queries
SIROCCO '08 Proceedings of the 15th international colloquium on Structural Information and Communication Complexity
Computing minimal doubly resolving sets of graphs
Computers and Operations Research
Discovery of network properties with all-shortest-paths queries
Theoretical Computer Science
On approximation complexity of metric dimension problem
IWOCA'10 Proceedings of the 21st international conference on Combinatorial algorithms
Topology discovery of sparse random graphs with few participants
Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Topology discovery of sparse random graphs with few participants
ACM SIGMETRICS Performance Evaluation Review - Performance evaluation review
Network verification via routing table queries
SIROCCO'11 Proceedings of the 18th international conference on Structural information and communication complexity
The covert set-cover problem with application to network discovery
WALCOM'10 Proceedings of the 4th international conference on Algorithms and Computation
Approximation complexity of Metric Dimension problem
Journal of Discrete Algorithms
Approximate discovery of random graphs
SAGA'07 Proceedings of the 4th international conference on Stochastic Algorithms: foundations and applications
On the complexity of metric dimension
ESA'12 Proceedings of the 20th Annual European conference on Algorithms
The (weighted) metric dimension of graphs: hard and easy cases
WG'12 Proceedings of the 38th international conference on Graph-Theoretic Concepts in Computer Science
On the metric dimension of line graphs
Discrete Applied Mathematics
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Due to its fast, dynamic, and distributed growth process, it is hard to obtain an accurate map of the Internet. In many cases, such a map-representing the structure of the Internet as a graph with nodes and links-is a prerequisite when investigating properties of the Internet. A common way to obtain such maps is to make certain local measurements at a small subset of the nodes, and then to combine these in order to "discover" (an approximation of) the actual graph. Each of these measurements is potentially quite costly. It is thus a natural objective to minimize the number of measurements which still discover the whole graph. We formalize this problem as a combinatorial optimization problem and consider it for two different models characterized by different types of measurements. We give several upper and lower bounds on the competitive ratio (for the online network discovery problem) and the approximation ratio (for the offline network verification problem) in both models. Furthermore, for one of the two models, we compare four simple greedy strategies in an experimental analysis