Paper Info
Title
Large-scale indexing of spatial data in distributed repositories: the SD-Rtree
Abstract
We propose a scalable distributed data structure (SDDS) called SD-Rtree. We intend our structure for point, window and kNN queries over large spatial datasets distributed on clusters of interconnected servers. The structure balances the storage and processing load over the available resources, and aims at minimizing the size of the cluster. SD-Rtree generalizes the well-known Rtree structure. It uses a distributed balanced binary tree that scales with insertions to potentially any number of storage servers through splits of the overloaded ones. A user/application manipulates the structure from a client node. The client addresses the tree through its image that can be possibly outdated due to later split. This may generate addressing errors, solved by the forwarding among the servers. Specific messages towards the clients incrementally correct the outdated images. We present the building of an SD-Rtree through insertions, focusing on the split and rotation algorithms. We follow with the query algorithms. We describe then a flexible allocation protocol which allows to cope with a temporary shortage of storage resources through data storage balancing. Experiments show additional aspects of SD-Rtree and compare its behavior with a distributed quadtree. The results justify our various design choices and the overall utility of the structure.
Year
DOI
Venue
2009
10.1007/s00778-009-0135-4
VLDB J.
Keywords
Field
DocType
Spatial indexing,Distributed structure
Data warehouse,Data mining,Computer science,Computer data storage,Server,Search engine indexing,Binary tree,Database,Spatial database,Scalability,Quadtree
Journal
Volume
Issue
ISSN
18
4
1066-8888
Citations 
PageRank 
References 
7
0.49
19
Authors
3
Name
Order
Citations
PageRank
Cédric du Mouza110014.67
Witold Litwin21937928.21
Philippe Rigaux3444110.71