Paper Info
Title
Scalable spatial information discovery over Distributed Hash Tables
Abstract
In this paper, we present a Peer-to-Peer (P2P) spatial information discovery system that enables spatial range queries over Distributed Hash Tables (DHTs). Our system utilizes a less-distorting octahedral map projection in contrast to the quadrilateral projections used by majority of the previously proposed systems, to represent the spatial information. We also introduce a Space-Filling Curve (SFC)-based data placement strategy that reduces the probability of data hot-spots in the network. Moreover, we show that our system achieves scalable resolution of location-based range queries, by utilizing a tree-based query optimization algorithm. Compared to the basic query resolution algorithm, the query optimization algorithm reduces the average number of parallel messages used to resolve a query, by a factor of 96%.
Year
DOI
Venue
2009
10.1145/1621890.1621892
COMSWARE
Keywords
Field
DocType
data hot-spots,location-based range query,hash tables,data placement strategy,query optimization algorithm,spatial information,scalable resolution,tree-based query optimization algorithm,spatial information discovery system,spatial range,scalable spatial information discovery,basic query resolution algorithm,hot spot,p2p,overlay network,distributed hash table,overlay networks,range query,query optimization
Query optimization,Data mining,Hash tree,Query expansion,Double hashing,Key-based routing,Computer science,Range query (data structures),Hash function,Spatial query
Conference
Citations 
PageRank 
References 
2
0.36
16
Authors
6
Name
Order
Citations
PageRank
Faraz Memon1383.20
Daniel Tiebler220.36
Frank Dürr350043.83
Kurt Rothermel42806450.84
Marco Tomsu5161.79
Peter Domschitz6332.53