Time-aggregated graphs for modeling spatio-temporal networks

Betsy George, Shashi Shekhar

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

23 Scopus citations


Given applications such as location based services and the spatio-temporal queries they may pose on a spatial network (eg. road networks), the goal is to develop a simple and expressive model that honors the time dependence of the road network. The model must support the design of efficient algorithms for computing the frequent queries on the network. This problem is challenging due to potentially conflicting requirements of model simplicity and support for efficient algorithms. Time expanded networks which have been used to model dynamic networks employ replication of the network across time instants, resulting in high storage overhead and algorithms that are computationally expensive. In contrast, the proposed time-aggregated graphs do not replicate nodes and edges across time; rather they allow the properties of edges and nodes to be modeled as a time series. Since the model does not replicate the entire graph for every instant of time, it uses less memory and the algorithms for common operations (e.g. connectivity, shortest path) are computationally more efficient than the time expanded networks.

Original languageEnglish (US)
Title of host publicationAdvances in Conceptual Modeling
Subtitle of host publicationTheory and Practice - ER 2006 Workshops BP-UML, CoMoGIS, COSS, ECDM, OIS, QoIS, SemWAT, Proceedings
PublisherSpringer Verlag
Number of pages15
ISBN (Print)3540477039, 9783540477037
StatePublished - 2006
Event25th International Conference on Conceptual Modeling, ER 2006 - Tucson, AZ, United States
Duration: Nov 6 2006Nov 9 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4231 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other25th International Conference on Conceptual Modeling, ER 2006
CountryUnited States
CityTucson, AZ


  • Location based services
  • Shortest paths
  • Spatio-temporal data-bases
  • Time-aggregated graphs


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