End-to-end routing behavior in the Internet
IEEE/ACM Transactions on Networking (TON)
On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
IDMaps: a global internet host distance estimation service
IEEE/ACM Transactions on Networking (TON)
Topology Discovery by Active Probing
SAINT-W '02 Proceedings of the 2002 Symposium on Applications and the Internet (SAINT) Workshops
The impact of DHT routing geometry on resilience and proximity
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Measuring ISP topologies with rocketfuel
IEEE/ACM Transactions on Networking (TON)
Vivaldi: a decentralized network coordinate system
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Implementing aggregation and broadcast over Distributed Hash Tables
ACM SIGCOMM Computer Communication Review
DIMES: let the internet measure itself
ACM SIGCOMM Computer Communication Review
Cyclone: A Novel Design Schema for Hierarchical DHTs
P2P '05 Proceedings of the Fifth IEEE International Conference on Peer-to-Peer Computing
New indices for cluster validity assessment
Pattern Recognition Letters
Stable and Accurate Network Coordinates
ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
On the accuracy of embeddings for internet coordinate systems
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Geographic locality of IP prefixes
IMC '05 Proceedings of the 5th 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
Inferring subnets in router-level topology collection studies
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Spurring adoption of DHTs with openhash, a public DHT service
IPTPS'04 Proceedings of the Third international conference on Peer-to-Peer Systems
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Designing topologically-aware overlays is a recurrent subject in peer-to-peer research. Although there exists a plethora of approaches, Internet coordinate systems such as GNP (which attempt to predict the pair-wise O(N^2) latencies between N nodes using only O(N) measurements) have become the most attractive approach to make the overlay connectivity structures congruent with the underlying IP-level network topology. With appropriate input, coordinate systems allow complex distributed problems to be solved geometrically, including multicast, server selection, etc. For these applications, and presumably others like that, exact topological information is not required and it is sufficient to use informative hints about the relative positions of Internet clients. Clustering operation, which attempts to partition a set of objects into several subsets that are distinguishable under some criterion of similarity, could significantly ease these operations. However, when the main objective is clustering nodes, Internet coordinate systems present strong limitations to identify the right clusters, a problem known as false clustering. In this work, the authors answer a fundamental question that has been obscured in proximity techniques so far: how often false clustering happens in reality and how much this affects the overall performance of an overlay. To that effect, the authors present a novel approach called TR-Clustering to cluster nodes in overlay networks based on their physical positions on the Internet. To be specific, TR-Clustering uses the Internet routers with high vertex betweenness centrality to cluster participating nodes. Informally, the betweenness centrality of a router is defined as the fraction of shortest paths between all pairs of nodes running through it. Simulation results illustrate that TR-Clustering is superior to existing techniques, with less than a 5% of falsely clustered peers (of course, relative to the datasets utilized in their evaluation).