PARINET: A tunable access method for in-network trajectories

Iulian Sandu Popa, Karine Zeitouni, Vincent Oria, Dominique Barth, Sandrine Vial

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

In this paper we propose PARINET, a new access method to efficiently retrieve the trajectories of objects moving in networks. The structure of PARINET is based on a combination of graph partitioning and a set of composite B+-tree local indexes. PARINET is designed for historical data and relies on the distribution of the data over the network as for historical data, the data distribution is known in advance. Because the network can be modeled using graphs, the partitioning of the trajectory data is based on graph partitioning theory and can be tuned for a given query load. The data in each partition is indexed on the time component using B+-trees. We study different types of queries, and provide an optimal configuration for several scenarios. PARINET can easily be integrated into any RDBMS, which is an essential asset particularly for industrial or commercial applications. The experimental evaluation under an off-the-shelf DBMS shows that PARINET is robust. It also significantly outperforms both MON-tree and another R-tree based access method which are the reference indexing techniques for in-network trajectory databases.

Original languageEnglish (US)
Title of host publication26th IEEE International Conference on Data Engineering, ICDE 2010 - Conference Proceedings
Pages177-188
Number of pages12
DOIs
StatePublished - Jun 1 2010
Event26th IEEE International Conference on Data Engineering, ICDE 2010 - Long Beach, CA, United States
Duration: Mar 1 2010Mar 6 2010

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627

Other

Other26th IEEE International Conference on Data Engineering, ICDE 2010
CountryUnited States
CityLong Beach, CA
Period3/1/103/6/10

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Information Systems

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