Detailed Information on Publication Record
2004
A Scalable Nearest Neighbor Search in P2P Systems
BATKO, Michal, Claudio GENNARO and Pavel ZEZULABasic information
Original name
A Scalable Nearest Neighbor Search in P2P Systems
Name in Czech
Škálovatelné hledaní nejbližších sousedů v P2P systémech
Authors
BATKO, Michal (203 Czech Republic), Claudio GENNARO (380 Italy) and Pavel ZEZULA (203 Czech Republic, guarantor)
Edition
Toronto, 2nd International VLDB Workshop on Databases, Information Systems and Peer-to-Peer Computing, p. 64-77, 14 pp. 2004
Publisher
VLDB Publishing
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
20206 Computer hardware and architecture
Country of publisher
Canada
Confidentiality degree
není předmětem státního či obchodního tajemství
RIV identification code
RIV/00216224:14610/04:00010338
Organization unit
Institute of Computer Science
UT WoS
000228552500006
Keywords in English
distributed data; scalable structures; similarity search; nearest neighbors
Tags
International impact, Reviewed
Změněno: 29/6/2009 14:42, RNDr. Michal Batko, Ph.D.
V originále
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.
In Czech
Rozšíření struktury pro podobnostní hledaní v P2P systémech o hledání nejbližších sousedů.
Links
| MSM 143300004, plan (intention) |
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