On Investigating Scalability and Robustness in a Self-organizing Retrieval System

SEDMIDUBSKÝ, Jan, Vlastislav DOHNAL and Pavel ZEZULA. On Investigating Scalability and Robustness in a Self-organizing Retrieval System. In Proceedings of CIKM 2011 and the co-located Workshops. New York, NY 10087-0777: ACM Digital Library, 2011, p. 33-38. ISBN 978-1-4503-0717-8.

Basic information

Original name

On Investigating Scalability and Robustness in a Self-organizing Retrieval System

Authors

SEDMIDUBSKÝ, Jan (203 Czech Republic, guarantor, belonging to the institution), Vlastislav DOHNAL (203 Czech Republic, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution)

Edition

New York, NY 10087-0777, Proceedings of CIKM 2011 and the co-located Workshops, p. 33-38, 6 pp. 2011

Publisher

ACM Digital Library

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Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United Kingdom of Great Britain and Northern Ireland

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

RIV identification code

RIV/00216224:14330/11:00049902

Organization unit

Faculty of Informatics

ISBN

978-1-4503-0717-8

Keywords in English

similarity search; scalability; robustness; self-organization

Tags

DISA

Tags

International impact, Reviewed

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Abstract

V originále

We introduce a self-organizing similarity search system for a large-scale unstructured peer-to-peer network, called the Metric Social Network. This system does not rely on any centralized control and does not define any data clustering or partitioning principle. It combines multiple strategies into a single system which results in abilities to scale to a large number of peers, to adapt to different data distributions, and to be robust to abrupt peer disconnections. We prove these abilities by running various experimental trials on real-life, as well as, synthetic data sets stored on up to 2,000 peers. Additionally, different data distributions among the peers, ranging from clustered to totally non-clustered and real-life data distributions, are also considered.

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Links

GA201/09/0683, research and development project	Name: Vyhledávání v rozsáhlých multimediálních databázích Investor: Czech Science Foundation, Similarity Searching in Very Large Multimedia Databases
VF20102014004, research and development project	Name: Multimediální analýza (Acronym: Multimediální analýza) Investor: Ministry of the Interior of the CR