Center for Measurement and Analysis of Network Data

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Current large-scale topology mapping systems require multiple days to characterize the Internet due to the large amount of probing traffic they incur. The accuracy of maps from existing systems is unknown, yet empirical evidence suggests that additional fine-grained probing exposes hidden links and temporal dynamics. Through longitudinal analysis of data from the Archipelago and iPlane systems, in conjunction with our own active probing, we examine how to shorten Internet topology mapping cycle time. In particular, this work develops discriminatory primitives that maximize topological fidelity while being efficient.
Papers: Talks: Public Code:
  • Yarrp: Yelling at Random Routers Progressively
  • Arkqueue: Topology on Demand Wrapper for CAIDA's Ark
  • scamper util: Native python implementation of scamper utils
  • degreaser: Scanner to find network tarpits
Center for Measurement and Analysis of Network Data