LH*—a scalable, distributed data structure
ACM Transactions on Database Systems (TODS)
Distance browsing in spatial databases
ACM Transactions on Database Systems (TODS)
A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
ACM Computing Surveys (CSUR)
D-Index: Distance Searching Index for Metric Data Sets
Multimedia Tools and Applications
Multi-dimensional range queries in sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Index-driven similarity search in metric spaces (Survey Article)
ACM Transactions on Database Systems (TODS)
An efficient nearest neighbor algorithm for P2P settings
dg.o '05 Proceedings of the 2005 national conference on Digital government research
Building and Querying a P2P Virtual World
Geoinformatica
M-Chord: a scalable distributed similarity search structure
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
On scalability of the similarity search in the world of peers
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
Efficient peer-to-peer semantic overlay networks based on statistical language models
P2PIR '06 Proceedings of the international workshop on Information retrieval in peer-to-peer networks
Energy-Efficient Data Dissemination Schemes for Nearest Neighbor Query Processing
IEEE Transactions on Computers
Scalability comparison of Peer-to-Peer similarity search structures
Future Generation Computer Systems
Efficient range query processing in metric spaces over highly distributed data
Distributed and Parallel Databases
A content-addressable network for similarity search in metric spaces
DBISP2P'05/06 Proceedings of the 2005/2006 international conference on Databases, information systems, and peer-to-peer computing
Metric-Based similarity search in unstructured peer-to-peer systems
Transactions on Large-Scale Data- and Knowledge-Centered Systems V
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Similarity search in metric spaces represents an important paradigm for content-based retrieval in many applications. Existing centralized search structures can speed-up retrieval, but they do not scale up to large volume of data because the response time is linearly increasing with the size of the searched file. In this article, we study the problem of executing the nearest neighbor(s) queries in a distributed metric structure, which is based on the P2P communication paradigm and the generalized hyperplane partitioning. By exploiting parallelism in a dynamic network of computers, the query execution scales up very well considering both the number of distance computations and the hop count between the peers. Results are verified by experiments on real-life data sets.