A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Supporting Multi-Dimensional Range Queries in Peer-to-Peer Systems
P2P '05 Proceedings of the Fifth IEEE International Conference on Peer-to-Peer Computing
A Location-Based Peer-to-Peer Network for Context-Aware Services in a Ubiquitous Environment
SAINT-W '05 Proceedings of the 2005 Symposium on Applications and the Internet Workshops
Generating Skip Delaunay Network for P2P Geocasting
C5 '08 Proceedings of the Sixth International Conference on Creating, Connecting and Collaborating through Computing (c5 2008)
Live e! project: sensing the earth
AINTEC'06 Proceedings of the Second Asian international conference on Technologies for Advanced Heterogeneous Networks
Long range contacts in overlay networks
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
Application-layer multicasting with Delaunay triangulation overlays
IEEE Journal on Selected Areas in Communications
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In this paper, we propose an overlay network called HDOV, a hierarchical extension of Delaunay overlay network for data collection with multiple spatial resolutions. By using HDOV, spatial data with at least specified spatial resolution can be collected reducing the redundant messages for data collection from wide area peer-to-peer network. The proposal in HDOV consists of 1) uniform node selection method for multiple spatial resolution levels and 2) hierarchical overlay network construction methods for the selected nodes. The proposed node selection method in HDOV probabilistically adjusts geographical node densities of the overlay network levels according to the size of the Voronoi cell of each node. We propose two types of hierarchical overlay network construction method: the Selected-Nodes Leading method (SNL) and the Unselected-Nodes Leading method (UNL). Our simulation results show that the proposed method can construct overlay networks that collect data with specified uniform spatial resolutions. The simulation results also show that the UNL requires low network construction cost especially in the skewed node distribution environment and the SNL requires less network reconstruction cost when there are no adjoined node failures.