SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
HyperCast: A Protocol for Maintaining Multicast Group Members in a Logical Hypercube Topology
NGC '99 Proceedings of the First International COST264 Workshop on Networked Group Communication
Cluster-preserving Embedding of Proteins
Cluster-preserving Embedding of Proteins
Application-Layer Multicasting with Delaunay Triangulation Overlays
Application-Layer Multicasting with Delaunay Triangulation Overlays
Comparison of image similarity queries in P2P systems
Computer Communications
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Crucial for the performance of Peer-to-Peer networks based on geometric topologies is the measurement complexity and quality of the mapping function used to map a node in the network to a point in the geometric target space. In this paper we study how results from mathematics as well as data mining can be applied to this mapping problem. Using a metric space model for networks and results from mathematics a relation between the number of nodes to be mapped, the worst case error of the mapping and the dimension of the geometric target space is formulated. As a main result Geometric Cluster Placement (GCP) is presented, an improved and resilient placement algorithm based on GNP. An evaluation of GCP presented is based on measurement data from the RIPE NCC Test Traffic Measurement (TTM) Project.