Trip Planner Over Probabilistic Time-Dependent Road Networks

Recently, the management of transportation systems has become increasingly important in many real applications such as location-based services, supply chain management, traffic control, and so on. These applications usually involve queries over spatial road networks with dynamically changing and complicated traffic conditions. In this paper, we model such a network by a probabilistic time-dependent graph (PT-Graph), whose edges are associated with uncertain delay functions. We propose a useful query in the PT-Graph, namely a trip planner query (TPQ), which retrieves trip plans that traverse a set of query points in PT-Graph, having the minimum traveling time with high confidence. To tackle the efficiency issue, we present the pruning methods time interval pruning and probabilistic pruning to effectively rule out false alarms of trip plans. Furthermore, we design a pre-computation technique based on the cost model and construct an index structure over the pre-computed data to enable the pruning via the index. We integrate our proposed pruning methods into an efficient query procedure to answer TPQs. Through extensive experiments, we demonstrate the efficiency and effectiveness of our TPQ query answering approach.

[1]  Heng Tao Shen,et al.  Multi-source Skyline Query Processing in Road Networks , 2007, 2007 IEEE 23rd International Conference on Data Engineering.

[2]  Peter J. Haas,et al.  MCDB: a monte carlo approach to managing uncertain data , 2008, SIGMOD Conference.

[3]  Xiang Lian,et al.  Efficient query answering in probabilistic RDF graphs , 2011, SIGMOD '11.

[4]  Michael I. Jordan Graphical Models , 2003 .

[5]  Chengfei Liu,et al.  Query Evaluation on Probabilistic RDF Databases , 2009, WISE.

[6]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[7]  Jian Li,et al.  A unified approach to ranking in probabilistic databases , 2009, The VLDB Journal.

[8]  Frederick Vu Central Limit Theorem , 2015 .

[9]  Elke A. Rundensteiner,et al.  Integrated query processing strategies for spatial path queries , 1997, Proceedings 13th International Conference on Data Engineering.

[10]  Yufei Tao,et al.  Reverse nearest neighbors in large graphs , 2006, IEEE Transactions on Knowledge and Data Engineering.

[11]  Pavel Zezula,et al.  M-tree: An Efficient Access Method for Similarity Search in Metric Spaces , 1997, VLDB.

[12]  Yoshio Fukushige Representing Probabilistic Relations in RDF , 2005, ISWC-URSW.

[13]  Michael Stonebraker,et al.  Heuristic search in database systems , 1986 .

[14]  Sunil Prabhakar,et al.  Evaluating probabilistic queries over imprecise data , 2003, SIGMOD '03.

[15]  Jeffrey Xu Yu,et al.  Finding time-dependent shortest paths over large graphs , 2008, EDBT '08.

[16]  Daisy Zhe Wang,et al.  BayesStore: managing large, uncertain data repositories with probabilistic graphical models , 2008, Proc. VLDB Endow..

[17]  Feifei Li,et al.  On Trip Planning Queries in Spatial Databases , 2005, SSTD.

[18]  Haixun Wang,et al.  Distance-Constraint Reachability Computation in Uncertain Graphs , 2011, Proc. VLDB Endow..

[19]  Christian S. Jensen,et al.  Path prediction and predictive range querying in road network databases , 2010, The VLDB Journal.

[20]  Tanzima Hashem,et al.  Group Trip Planning Queries in Spatial Databases , 2013, SSTD.

[21]  Yufei Tao,et al.  Indexing Multi-Dimensional Uncertain Data with Arbitrary Probability Density Functions , 2005, VLDB.

[22]  Dan Suciu,et al.  Efficient query evaluation on probabilistic databases , 2004, The VLDB Journal.

[23]  H. V. Jagadish,et al.  Direct transitive closure algorithms: design and performance evaluation , 1990, TODS.

[24]  Christian S. Jensen,et al.  Techniques for efficient road-network-based tracking of moving objects , 2005, IEEE Transactions on Knowledge and Data Engineering.

[25]  Raghu Ramakrishnan,et al.  Transitive closure algorithms based on graph traversal , 1993, TODS.

[26]  Hans-Peter Kriegel,et al.  The R*-tree: an efficient and robust access method for points and rectangles , 1990, SIGMOD '90.

[27]  George Kollios,et al.  k-nearest neighbors in uncertain graphs , 2010, Proc. VLDB Endow..

[28]  Yufei Tao,et al.  Query Processing in Spatial Network Databases , 2003, VLDB.

[29]  Bin Jiang,et al.  Probabilistic Skylines on Uncertain Data , 2007, VLDB.

[30]  Jian Pei,et al.  Probabilistic path queries in road networks: traffic uncertainty aware path selection , 2010, EDBT '10.

[31]  Cyrus Shahabi,et al.  A Road Network Embedding Technique for K-Nearest Neighbor Search in Moving Object Databases , 2002, GIS '02.

[32]  Michael Stonebraker,et al.  Heuristic Search in Data Base Systems , 1984, Expert Database Workshop.