%0 Book Section %1 noKey %A George, Betsy %A Shekhar, Shashi %B Advances in Conceptual Modeling - Theory and Practice %D 2006 %E Roddick, JohnF. %E Benjamins, V.Richard %E Si-said Cherfi, Samira %E Chiang, Roger %E Claramunt, Christophe %E Elmasri, RamezA. %E Grandi, Fabio %E Han, Hyoil %E Hepp, Martin %E Lytras, MiltiadisD. %E Mišić, VojislavB. %E Poels, Geert %E Song, Il-Yeol %E Trujillo, Juan %E Vangenot, Christelle %I Springer Berlin Heidelberg %K RelatedWork TimeDepedent %P 85-99 %R 10.1007/11908883_12 %T Time-Aggregated Graphs for Modeling Spatio-temporal Networks %U http://dx.doi.org/10.1007/11908883_12 %V 4231 %X 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. %@ 978-3-540-47703-7

@incollection{noKey, abstract = {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.}, added-at = {2013-06-25T14:46:16.000+0200}, author = {George, Betsy and Shekhar, Shashi}, biburl = {https://www.bibsonomy.org/bibtex/214c6c835d802fb55c50e403d25042d02/macek}, booktitle = {Advances in Conceptual Modeling - Theory and Practice}, description = {Time-Aggregated Graphs for Modeling Spatio-temporal Networks - Springer}, doi = {10.1007/11908883_12}, editor = {Roddick, JohnF. and Benjamins, V.Richard and Si-said Cherfi, Samira and Chiang, Roger and Claramunt, Christophe and Elmasri, RamezA. and Grandi, Fabio and Han, Hyoil and Hepp, Martin and Lytras, MiltiadisD. and Mišić, VojislavB. and Poels, Geert and Song, Il-Yeol and Trujillo, Juan and Vangenot, Christelle}, interhash = {4fcbed48cc012e4e71b96ce1f6a47af9}, intrahash = {14c6c835d802fb55c50e403d25042d02}, isbn = {978-3-540-47703-7}, keywords = {RelatedWork TimeDepedent}, pages = {85-99}, publisher = {Springer Berlin Heidelberg}, series = {Lecture Notes in Computer Science}, timestamp = {2013-06-25T14:46:16.000+0200}, title = {Time-Aggregated Graphs for Modeling Spatio-temporal Networks}, url = {http://dx.doi.org/10.1007/11908883_12}, volume = 4231, year = 2006 }