Presentazione, 2004, ENG

A Scalable Nearest Neighbor Search in P2P Systems

Batko M.; Gennaro C.; Zezula P.

Masaryk University Brno, Czech Republic; CNR-ISTI, Pisa, Italy; Masaryk University Brno, Czech Republic

Similarity search in metric spaces represents an important paradigm for content-based retrieval of 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.

International Workshop on Databases, Information Systems and Peer-to-Peer Computing, pp. 1–14, Toronto, Canada, 29-30 August 2004

Keywords

Metric space, Similarity search, Peer-to-peer, Grid

CNR authors

Gennaro Claudio

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

ID: 120474

Year: 2004

Type: Presentazione

Creation: 2009-06-16 00:00:00.000

Last update: 2019-12-10 17:56:57.000

CNR authors

External links

OAI-PMH: Dublin Core

OAI-PMH: Mods

OAI-PMH: RDF

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:120474

ISI Web of Science (WOS): 000228552500006