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)
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Efficient User-Adaptable Similarity Search in Large Multimedia Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Dynamically Fault-Tolerant Content Addressable Networks
IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
Application-Level Multicast Using Content-Addressable Networks
NGC '01 Proceedings of the Third International COST264 Workshop on Networked Group Communication
Peer-to-peer information retrieval using self-organizing semantic overlay networks
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
D-Index: Distance Searching Index for Metric Data Sets
Multimedia Tools and Applications
MAAN: A Multi-Attribute Addressable Network for Grid Information Services
GRID '03 Proceedings of the 4th International Workshop on Grid Computing
Index-driven similarity search in metric spaces (Survey Article)
ACM Transactions on Database Systems (TODS)
Load balancing and locality in range-queriable data structures
Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing
Mercury: supporting scalable multi-attribute range queries
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
One torus to rule them all: multi-dimensional queries in P2P systems
Proceedings of the 7th International Workshop on the Web and Databases: colocated with ACM SIGMOD/PODS 2004
SWAM: a family of access methods for similarity-search in peer-to-peer data networks
Proceedings of the thirteenth ACM international conference on Information and knowledge management
A Distributed Quadtree Index for Peer-to-Peer Settings
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
An efficient nearest neighbor algorithm for P2P settings
dg.o '05 Proceedings of the 2005 national conference on Digital government research
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
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
SkipNet: a scalable overlay network with practical locality properties
USITS'03 Proceedings of the 4th conference on USENIX Symposium on Internet Technologies and Systems - Volume 4
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
Similarity grid for searching in metric spaces
DELOS'04 Proceedings of the 6th Thematic conference on Peer-to-Peer, Grid, and Service-Orientation in Digital Library Architectures
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Most of the Peer-to-Peer search techniques proposed in the recent years have focused on the single-key retrieval. However, similarity search in metric spaces represents an important paradigm for content-based retrieval in many applications. In this paper we introduce an extension of the well-known Content-Addressable Network paradigm to support storage and retrieval of more generic metric space objects. In particular we address the problem of executing the nearest neighbors queries, and propose three different algorithms of query execution. An extensive experimental study on real-life data sets explores the performance characteristics of the proposed algorithms by showing their advantages and disadvantages.