Scalable spatial information discovery over Distributed Hash Tables

  • Authors:
  • Faraz Memon;Daniel Tiebler;Frank Dürr;Kurt Rothermel;Marco Tomsu;Peter Domschitz

  • Affiliations:
  • Universität Stuttgart, Stuttgart, Germany;Universität Stuttgart, Stuttgart, Germany;Universität Stuttgart, Stuttgart, Germany;Universität Stuttgart, Stuttgart, Germany;Bell Laboratories Alcatel--Lucent, Stuttgart, Germany;Bell Laboratories Alcatel--Lucent, Stuttgart, Germany

  • Venue:
  • Proceedings of the Fourth International ICST Conference on COMmunication System softWAre and middlewaRE
  • Year:
  • 2009

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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%.