Using a distributed quadtree index in peer-to-peer networks

Peer-to-peer (P2P) networks have become a powerful means for online data exchange. Currently, users are primarily utilizing these networks to perform exact-match queries and retrieve complete files. However, future more data intensive applications, such as P2P auction networks, P2P job-search networ...

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Vydáno v:The VLDB journal Ročník 16; číslo 2; s. 165 - 178
Hlavní autoři: Tanin, Egemen, Harwood, Aaron, Samet, Hanan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Heidelberg Springer 01.04.2007
Témata:
Applied sciences
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Exact sciences and technology
Information systems. Data bases
Memory organisation. Data processing
Software
File query
High performance
Spatial data structures
Data type
Peer to peer
Bidding
Database query
Peer-to-peer networks
Quadtrees
Very large databases
Information retrieval
Distributed system
Distributed computing
Range query
Computational geometry
Video game
Multidimensional database
Distributed data structures
Load balancing
Quad tree
Data structure
Spatial database
ISSN:1066-8888, 0949-877X
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Shrnutí:Peer-to-peer (P2P) networks have become a powerful means for online data exchange. Currently, users are primarily utilizing these networks to perform exact-match queries and retrieve complete files. However, future more data intensive applications, such as P2P auction networks, P2P job-search networks, P2P multiplayer games, will require the capability to respond to more complex queries such as range queries involving numerous data types including those that have a spatial component. In this paper, a distributed quadtree index that adapts the MX-CIF quadtree is described that enables more powerful accesses to data in P2P networks. This index has been implemented for various prototype P2P applications and results of experiments are presented. Our index is easy to use, scalable, and exhibits good load-balancing properties. Similar indices can be constructed for various multidimensional data types with both spatial and non-spatial components.
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ISSN:1066-8888
0949-877X
DOI:10.1007/s00778-005-0001-y