On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Measuring ISP topologies with rocketfuel
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
PlanetLab: an overlay testbed for broad-coverage services
ACM SIGCOMM Computer Communication Review
DIMES: let the internet measure itself
ACM SIGCOMM Computer Communication Review
Avoiding traceroute anomalies with Paris traceroute
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
iPlane: an information plane for distributed services
OSDI '06 Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7
Measuring load-balanced paths in the internet
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Internet Mapping: From Art to Science
CATCH '09 Proceedings of the 2009 Cybersecurity Applications & Technology Conference for Homeland Security
Where the sidewalk ends: extending the internet as graph using traceroutes from P2P users
Proceedings of the 5th international conference on Emerging networking experiments and technologies
Predicting and tracking internet path changes
Proceedings of the ACM SIGCOMM 2011 conference
INTERNET TOPOLOGY DISCOVERY: A SURVEY
IEEE Communications Surveys & Tutorials
Toward fast and efficient IP-level network topology capture
Proceedings of the 2012 ACM conference on CoNEXT student workshop
Efficient IP-Level network topology capture
PAM'13 Proceedings of the 14th international conference on Passive and Active Measurement
| Hi-index | 0.00 |
Network topology discovery with distributed traceroute-based measurement systems is important to monitor, measure, diagnose and capture IP-level network topology dynamism. Depending on the discovered topology size and the captured topology dynamism accuracy, a compromise has to be done regarding the measurement time granularity and the scale of these measurement systems. In this paper, we present our large-scale measurement dataset, and analysis of the network topology dynamism captured in a real measurement scenario. We also quantify the missed dynamism information with coarser measurement time granularity inferred by our proposed algorithm. These results confirm that probing less frequently, as it is the case of most of the existing measurement systems today, can dramatically affect the dynamism information captured.