Research Article
Scalable Spatial Information Discovery over Distributed Hash Tables
@INPROCEEDINGS{10.1145/1621890.1621892, author={Faraz Memon and Daniel Tiebler and Marco Tomsu and Peter Domschitz and Frank D\'{y}rr and Kurt Rothermel}, title={Scalable Spatial Information Discovery over Distributed Hash Tables}, proceedings={4th International ICST Conference on Communication System Software and Middleware}, publisher={ACM}, proceedings_a={COMSWARE}, year={2010}, month={5}, keywords={Peer-to-Peer overlay networks spatial information discovery location- based queries space-filling curves distributed hash tables}, doi={10.1145/1621890.1621892} }- Faraz Memon
Daniel Tiebler
Marco Tomsu
Peter Domschitz
Frank Dürr
Kurt Rothermel
Year: 2010
Scalable Spatial Information Discovery over Distributed Hash Tables
COMSWARE
ACM
DOI: 10.1145/1621890.1621892
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%.
