55 Citations (Scopus)

Abstract

A fundamental problem in large scale, decentralized distributed systems is the efficient discovery of information. This paper presents Squid, a peer-to-peer information discovery system that supports flexible searches and provides search guarantees. The fundamental concept underlying the approach is the definition of multi-dimensional information spaces and the maintenance of locality in these spaces. The key innovation is a dimensionality reducing indexing scheme that effectively maps the multi-dimensional information space to physical peers while preserving lexical locality. Squid supports complex queries containing partial keywords, wildcards and ranges. Analytical and simulation results show that Squid is scalable and efficient.

Original languageEnglish (US)
Pages (from-to)962-975
Number of pages14
JournalJournal of Parallel and Distributed Computing
Volume68
Issue number7
DOIs
StatePublished - Jul 1 2008

Fingerprint

SQUID
Innovation
Locality
Peer to Peer
Indexing
Decentralized
Dimensionality
Distributed Systems
Maintenance
Query
Partial
Range of data
Simulation

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications

Keywords

  • Distributed hash table
  • Information discovery
  • Peer-to-peer

Cite this

@article{c33b3df663984f9f9c0668b7e78a6b1d,
title = "Squid: Enabling search in DHT-based systems",
abstract = "A fundamental problem in large scale, decentralized distributed systems is the efficient discovery of information. This paper presents Squid, a peer-to-peer information discovery system that supports flexible searches and provides search guarantees. The fundamental concept underlying the approach is the definition of multi-dimensional information spaces and the maintenance of locality in these spaces. The key innovation is a dimensionality reducing indexing scheme that effectively maps the multi-dimensional information space to physical peers while preserving lexical locality. Squid supports complex queries containing partial keywords, wildcards and ranges. Analytical and simulation results show that Squid is scalable and efficient.",
keywords = "Distributed hash table, Information discovery, Peer-to-peer",
author = "Cristina Schmidt and Manish Parashar",
year = "2008",
month = "7",
day = "1",
doi = "https://doi.org/10.1016/j.jpdc.2008.02.003",
language = "English (US)",
volume = "68",
pages = "962--975",
journal = "Journal of Parallel and Distributed Computing",
issn = "0743-7315",
publisher = "Academic Press Inc.",
number = "7",

}

Squid : Enabling search in DHT-based systems. / Schmidt, Cristina; Parashar, Manish.

In: Journal of Parallel and Distributed Computing, Vol. 68, No. 7, 01.07.2008, p. 962-975.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Squid

T2 - Enabling search in DHT-based systems

AU - Schmidt, Cristina

AU - Parashar, Manish

PY - 2008/7/1

Y1 - 2008/7/1

N2 - A fundamental problem in large scale, decentralized distributed systems is the efficient discovery of information. This paper presents Squid, a peer-to-peer information discovery system that supports flexible searches and provides search guarantees. The fundamental concept underlying the approach is the definition of multi-dimensional information spaces and the maintenance of locality in these spaces. The key innovation is a dimensionality reducing indexing scheme that effectively maps the multi-dimensional information space to physical peers while preserving lexical locality. Squid supports complex queries containing partial keywords, wildcards and ranges. Analytical and simulation results show that Squid is scalable and efficient.

AB - A fundamental problem in large scale, decentralized distributed systems is the efficient discovery of information. This paper presents Squid, a peer-to-peer information discovery system that supports flexible searches and provides search guarantees. The fundamental concept underlying the approach is the definition of multi-dimensional information spaces and the maintenance of locality in these spaces. The key innovation is a dimensionality reducing indexing scheme that effectively maps the multi-dimensional information space to physical peers while preserving lexical locality. Squid supports complex queries containing partial keywords, wildcards and ranges. Analytical and simulation results show that Squid is scalable and efficient.

KW - Distributed hash table

KW - Information discovery

KW - Peer-to-peer

UR - http://www.scopus.com/inward/record.url?scp=44449088822&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=44449088822&partnerID=8YFLogxK

U2 - https://doi.org/10.1016/j.jpdc.2008.02.003

DO - https://doi.org/10.1016/j.jpdc.2008.02.003

M3 - Article

VL - 68

SP - 962

EP - 975

JO - Journal of Parallel and Distributed Computing

JF - Journal of Parallel and Distributed Computing

SN - 0743-7315

IS - 7

ER -