Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on uniform random number generation
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
IEEE/ACM Transactions on Networking (TON)
In search of path diversity in ISP networks
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Optimizing Network Performance In Replicated Hosting
WCW '05 Proceedings of the 10th International Workshop on Web Content Caching and Distribution
Exploiting internet route sharing for large scale available bandwidth estimation
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
CoNEXT '06 Proceedings of the 2006 ACM CoNEXT conference
Internet Mapping: From Art to Science
CATCH '09 Proceedings of the 2009 Cybersecurity Applications & Technology Conference for Homeland Security
A measurement study of internet delay asymmetry
PAM'08 Proceedings of the 9th international conference on Passive and active network measurement
Improved algorithms for network topology discovery
PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
INTERNET TOPOLOGY DISCOVERY: A SURVEY
IEEE Communications Surveys & Tutorials
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The performance of several Internet applications often relies on the measurability of path similarity between different participants. In particular, the performance of content distribution networks mainly relies on the awareness of content sources topology information. It is commonly admitted nowadays that, in order to ensure either path redundancy or efficient content replication, topological similarities between sources is evaluated by exchanging raw traceroute data, and by a hop by hop comparison of the IP topology observed from the sources to the several hundred or thousands of destinations. In this paper, based on real data we collected, we advocate that path similarity comparisons between different Internet entities can be much simplified using lossy coding techniques, such as Bloom filters, to exchange compressed topology information. The technique we introduce to evaluate path similarity enforces both scalability and data confidentiality while maintaining a high level of accuracy. In addition, we demonstrate that our technique is scalable as it requires a small amount of active probing and is not targets dependent.