A Safe-Region Approach to a Moving k-RNN Queries in a Directed Road Network

In road networks, k-range nearest neighbor (k-RNN) queries locate the k-closest neighbors for every point on the road segments, within a given query region defined by the user, based on the network distance. This is an important task because the user's location information may be inaccurate; furthermore, users may be unwilling to reveal their exact location for privacy reasons. Therefore, under this type of specific situation, the server returns candidate objects for every point on the road segments and the client evaluates and chooses exact k nearest objects from the candidate objects. Evaluating the query results at each timestamp to keep the freshness of the query answer, while the query object is moving, will create significant computation burden for the client. We therefore propose an efficient approach called a safe-region-based approach (SRA) for computing a safe segment region and the safe exit points of a moving nearest neighbor (NN) query in a road network. SRA avoids evaluation of candidate answers returned by the location-based server since it will have high computation cost in the query side. Additionally, we applied SRA for a directed road network, where each road network has a particular orientation and the network distances are not symmetric. Our experimental results demonstrate that SRA significantly outperforms a conventional solution in terms of both computational and communication costs.

[1]  Yufei Tao,et al.  Continuous Nearest Neighbor Search , 2002, VLDB.

[2]  Yunjun Gao,et al.  Continuous visible nearest neighbor query processing in spatial databases , 2010, The VLDB Journal.

[3]  Suman Nath,et al.  Approximate Evaluation of Range Nearest Neighbor Queries with Quality Guarantee , 2009, SSTD.

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

[5]  Kyriakos Mouratidis,et al.  Anonymous Query Processing in Road Networks , 2010, IEEE Transactions on Knowledge and Data Engineering.

[6]  Tae-Sun Chung,et al.  A collaborative approach to moving k-nearest neighbor queries in directed and dynamic road networks , 2015, Pervasive Mob. Comput..

[7]  Marco Gruteser,et al.  USENIX Association , 1992 .

[8]  Man Lung Yiu,et al.  A safe-exit approach for efficient network-based moving range queries , 2012, Data Knowl. Eng..

[9]  Roger Zimmermann,et al.  Privacy Protected Spatial Query Processing for Advanced Location Based Services , 2009, Wirel. Pers. Commun..

[10]  Stavros Papadopoulos,et al.  Nearest neighbor search with strong location privacy , 2010, Proc. VLDB Endow..

[11]  Chi-Yin Chow,et al.  Efficient Evaluation of k-Range Nearest Neighbor Queries in Road Networks , 2010, 2010 Eleventh International Conference on Mobile Data Management.

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

[13]  Cyrus Shahabi,et al.  Voronoi-Based K Nearest Neighbor Search for Spatial Network Databases , 2004, VLDB.

[14]  Farnoush Banaei Kashani,et al.  Efficient Continuous Nearest Neighbor Query in Spatial Networks Using Euclidean Restriction , 2009, SSTD.

[15]  Ying Cai,et al.  Design, analysis, and implementation of a large-scale real-time location-based information sharing system , 2008, MobiSys '08.

[16]  Wei-Shinn Ku,et al.  PROS: a peer-to-peer system for location privacy protection on road networks , 2009, GIS.

[17]  Yufei Tao,et al.  Time-parameterized queries in spatio-temporal databases , 2002, SIGMOD '02.

[18]  Ralf Hartmut Güting,et al.  Supporting uncertainty in moving objects in network databases , 2005, GIS '05.

[19]  Jianliang Xu,et al.  Fast Nearest Neighbor Search on Road Networks , 2006, EDBT.

[20]  Frank Stajano,et al.  Mix zones: user privacy in location-aware services , 2004, IEEE Annual Conference on Pervasive Computing and Communications Workshops, 2004. Proceedings of the Second.

[21]  Naphtali Rishe,et al.  Management of Dynamic Location Information in DOMINO , 2002, EDBT.

[22]  Muhammad Aamir Cheema,et al.  Efficient Algorithms to Monitor Continuous Constrained k Nearest Neighbor Queries , 2010, DASFAA.

[23]  Hanan Samet,et al.  Scalable network distance browsing in spatial databases , 2008, SIGMOD Conference.

[24]  Dieter Pfoser,et al.  Capturing the Uncertainty of Moving-Object Representations , 1999, SSD.

[25]  Heng Tao Shen,et al.  Monitoring path nearest neighbor in road networks , 2009, SIGMOD Conference.

[26]  Chin-Wan Chung,et al.  An Efficient and Scalable Approach to CNN Queries in a Road Network , 2005, VLDB.

[27]  Jianliang Xu,et al.  Grid-partition index: a hybrid method for nearest-neighbor queries in wireless location-based services , 2005, The VLDB Journal.

[28]  Yufei Tao,et al.  Efficient Evaluation of Probabilistic Advanced Spatial Queries on Existentially Uncertain Data , 2009, IEEE Transactions on Knowledge and Data Engineering.

[29]  Ling Liu,et al.  Privacy-Aware Mobile Services over Road Networks , 2009, Proc. VLDB Endow..