Article in Proceedings INPROC-2009-42

BibliographyMemon, Faraz; Tiebler, Daniel; Dürr, Frank; Rothermel, Kurt; Tomsu, Marco; Domschitz, Peter: Scalable Spatial Information Discovery over Distributed Hash Tables.
In: Procs. of 4th International Conference on COMmunication System softWAre and middlewaRE (COMSWARE'09), Dublin, Ireland, June 2009. ACM..
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 1-12, english.
ACM, June 2009.
Article in Proceedings (Conference Paper).
CR-SchemaC.2.1 (Network Architecture and Design)
H.3.3 (Information Search and Retrieval)
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%.

Full text and
other links
PDF (2871140 Bytes)
The original publication is available at ACM Digital Library
Copyright© ACM, 2009. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in proceedings of 4th International Conference on COMmunication System softWAre and middlewaRE (COMSWARE'09), pages 1-12, Dublin, Ireland, June 2009. http://doi.acm.org/10.1145/1621890.1621892
Department(s)University of Stuttgart, Institute of Parallel and Distributed Systems, Distributed Systems
Project(s)SuperP2P Multimedia Framework
Entry dateApril 21, 2009
   Publ. Department   Publ. Institute   Publ. Computer Science