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Processing Moving Queries over Moving Objects Using Motion-Adaptive Indexes
May 2006 (vol. 18 no. 5)
pp. 651-668
ASCII Text
x 
 
Bugra Gedik, Kun-Lung Wu, Philip S. Yu, Ling Liu, "Processing Moving Queries over Moving Objects Using Motion-Adaptive Indexes," IEEE Transactions on Knowledge and Data Engineering, vol. 18, no. 5, pp. 651-668, May, 2006.
 
 
BibTex
x
 
@article{ 10.1109/TKDE.2006.81,
author = {Bugra Gedik and Kun-Lung Wu and Philip S. Yu and Ling Liu},
title = {Processing Moving Queries over Moving Objects Using Motion-Adaptive Indexes},
journal ={IEEE Transactions on Knowledge and Data Engineering},
volume = {18},
number = {5},
issn = {1041-4347},
year = {2006},
pages = {651-668},
doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2006.81},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Knowledge and Data Engineering
TI - Processing Moving Queries over Moving Objects Using Motion-Adaptive Indexes
IS - 5
SN - 1041-4347
SP651
EP668
EPD - 651-668
A1 - Bugra Gedik,
A1 - Kun-Lung Wu,
A1 - Philip S. Yu,
A1 - Ling Liu,
PY - 2006
KW - Moving object databases
KW - spatio-temporal indexing
KW - continual queries.
VL - 18
JA - IEEE Transactions on Knowledge and Data Engineering
ER -
 
Bugra Gedik, IEEE Computer Society
Ling Liu, IEEE
This paper describes a motion-adaptive indexing scheme for efficient evaluation of moving continual queries (MCQs) over moving objects. It uses the concept of motion-sensitive bounding boxes (MSBs) to model moving objects and moving queries. These bounding boxes automatically adapt their sizes to the dynamic motion behaviors of individual objects. Instead of indexing frequently changing object positions, we index less frequently changing object and query MSBs, where updates to the bounding boxes are needed only when objects and queries move across the boundaries of their boxes. This helps decrease the number of updates to the indexes. More importantly, we use predictive query results to optimistically precalculate query results, decreasing the number of searches on the indexes. Motion-sensitive bounding boxes are used to incrementally update the predictive query results. Furthermore, we introduce the concepts of guaranteed safe radius and optimistic safe radius to extend our motion-adaptive indexing scheme to evaluating moving continual k\hbox{-}{\rm nearest\ neighbor\ }(k\rm NN) queries. Our experiments show that the proposed motion-adaptive indexing scheme is efficient for the evaluation of both moving continual range queries and moving continual k\rm NN queries.

[1] C.C. Aggarwal and D. Agrawal, “On Nearest Neighbor Indexing of Nonlinear Trajectories,” Proc. ACM Principles of Database Systems (PODS), pp. 252-259, 2003.
[2] R. Benetis, C.S. Jensen, G. Karciauskas, and S. Saltenis, “Nearest Neighbor and Reverse Nearest Neighbor Queries for Moving Objects,” Proc. Int'l Database Eng. and Applications Symp. (IDEAS), pp. 44-53, 2002.
[3] Y. Cai and K.A. Hua, “An Adaptive Query Management Technique for Efficient Real-Time Monitoring of Spatial Regions in Mobile Database Systems,” Proc. IEEE Int'l Performance Computing and Comm. Conf. (IPCCC), pp. 259-266, 2002.
[4] A. Civilis, C.S. Jensen, J. Nenortaite, and S. Pakalnis, “Efficient Tracking of Moving Objects with Precision Guarantees,” Proc. Int'l Conf. Mobile and Ubiquitous Systems (MobiQuitous), pp. 164-173, 2004.
[5] R.M. Fujimoto, Parallel and Distributed Simulation Systems. Wiley-Interscience, 2000.
[6] V. Gaede and O. Gunther, “Multidimensional Access Methods,” ACM Computing Surveys, vol. 30, no. 2, pp. 170-231, 1998.
[7] B. Gedik and L. Liu, “MobiEyes: Distributed Processing of Continuously Moving Queries on Moving Objects in a Mobile System,” Proc. Int'l Conf. Extending Database Technology (EDBT), 2004.
[8] B. Gedik, K.-L. Wu, P.S. Yu, and L. Liu, “Motion Adaptive Indexing for Moving Continual Queries over Moving Objects,” Proc. ACM Conf. Information and Knowledge Management (CIKM), 2004.
[9] S. Ilarri, E. Mena, and A. Illarramendi, “A System Based on Mobile Agents for Tracking Objects in a Location-Dependent Query Processing Environment,” Proc. Int'l Workshop Database and Expert Systems Applications (DEXA), pp. 577-581, 2001.
[10] C.S. Jensen, D. Lin, and B.C. Ooi, “Query and Update Efficient B+-Tree Based Indexing of Moving Objects,” Proc. Int'l Conf. Very Large Data Bases (VLDB), pp. 768-779, 2004.
[11] D.V. Kalashnikov, S. Prabhakar, S. Hambrusch, and W. Aref, “Efficient Evaluation of Continuous Range Queries on Moving Objects,” Proc. Database and Expert Systems Applications (DEXA), pp. 731-740, 2002.
[12] G. Kollios, D. Gunopulos, and V.J. Tsotras, “On Indexing Mobile Objects,” Proc. ACM Principles of Database Systems (PODS), pp. 261-272, 1999.
[13] I. Lazaridis, K. Porkaew, and S. Mehrotra, “Dynamic Queries over Mobile Objects,” Proc. Int'l Conf. Extending Database Technology (EDBT), pp. 269-286, 2002.
[14] L. Liu, C. Pu, and W. Tang, “Continual Queries for Internet Scale Event-Driven Information Delivery,” IEEE Trans. Knowledge and Data Eng., pp. 610-628, 1999.
[15] M.F. Mokbel, X. Xiong, and W.G. Aref, “SINA: Scalable Incremental Processing of Continuous Queries in Spatio-Temporal Databases,” Proc. ACM Special Interest Group on Management of Data Conf. (SIGMOD), pp. 321-330, 2004.
[16] B.W. Parkinson, J.J. Spilker, P. Axelrad, and P. Eng, Global Positioning System: Theory and Applications, Vol. 2. Am. Inst. Aeronautics and Astronautics, 1996.
[17] J.M. Patel, Y. Chen, and V.P. Chakka, “Stripes: An Efficient index for Predicted Trajectories,” Proc. ACM Special Interest Group on Management of Data Conf. (SIGMOD), pp. 637-646, 2004.
[18] D. Pfoser, C.S. Jensen, and Y. Theodoridis, “Novel Approaches in Query Processing for Moving Object Trajectories,” Proc. Very Large Data Bases Conf. (VLDB), pp. 395-406, 2000.
[19] S. Prabhakar, Y. Xia, D.V. Kalashnikov, W.G. Aref, and S.E. Hambrusch, “Query Indexing and Velocity Constrained Indexing,” IEEE Trans. Computers, vol. 51, no. 10, pp. 1124-1140, Oct. 2002.
[20] S. Saltenis, C.S. Jensen, S.T. Leutenegger, and M.A. Lopez, “Indexing the Positions of Continuously Moving Objects,” Proc. ACM Special Interest Group on Management of Data Conf. (SIGMOD), 2000.
[21] Z. Song and N. Roussopoulos, “Hashing Moving Objects,” Proc. IEEE Mobile Data Management, 2001.
[22] Z. Song and N. Roussopoulos, “$k\rm\hbox{-}Nearest$ Neighbor Search for Moving Query Point,” Proc. Symp. Spatial and Temporal Databases (SSTD), 2001.
[23] Y. Tao, D. Papadias, and Q. Shen, “Continuous Nearest Neighbor Search,” Proc. Int'l Conf. Very Large Data Bases, 2002.
[24] Y. Tao, D. Papadias, and J. Sun, “The $\rm TPR^*\hbox{-}Tree$ : An Optimized Spatio-Temporal Access Method for Predictive Queries,” Proc. Very Large Data Bases Conf. (VLDB), 2003.
[25] D.B. Terry, D. Goldberg, D. Nichols, and B.M. Oki, “Continuous Queries over Append-Only Database,” Proc. ACM Special Interest Group on Management of Data Conf. (SIGMOD), 1992.
[26] Y. Theodoridis, E. Stefanakis, and T. Sellis, “Efficient Cost Models for Spatial Queries Using R-Trees,” IEEE Trans. Knowledge and Data Eng., vol. 12, no. 1, pp. 19-32, Jan./Feb. 2000.
[27] O. Wolfson, “Moving Objects Information Management: The Database Challenge,” Proc. Next Generation Information Technologies and Systems, 2002.
[28] O. Wolfson, A.P. Sistla, S. Chamberlain, and Y. Yesha, “Updating and Querying Databases that Track Mobile Units,” Distributed and Parallel Databases, vol. 7, no. 3, pp. 257-387, 1999.
[29] K.-L. Wu, S.-K. Chen, and P.S. Yu, “Processing Continual Range Queries over Moving Objects Using VCR-Based Query Indexes,” Proc. Int'l Conf. Mobile and Ubiquitous Systems (MobiQuitous), 2004.
[30] K.-L. Wu, S.-K. Chen, and P.S. Yu, “On Incremental Processing of Continual Range Queries for Location-Aware Services and Applications,” Proc. Int'l Conf. Mobile and Ubiquitous Systems (MobiQuitous), 2005.
[31] X. Xiong, M.F. Mokbel, and W.G. Aref, “SEA-CNN: Scalable Processing of Continuous k-Nearest Neighbor Queries in Spatio-Temporal Databases,” Proc. IEEE Int'l Conf. Data Eng., 2005.
[32] X. Yu, K.Q. Pu, and N. Koudas, “Monitoring K-Nearest Neighbor Queries over Moving Objects,” Proc. IEEE Int'l Conf. Data Eng., 2005.

Index Terms:
Moving object databases, spatio-temporal indexing, continual queries.
Citation:
Bugra Gedik, Kun-Lung Wu, Philip S. Yu, Ling Liu, "Processing Moving Queries over Moving Objects Using Motion-Adaptive Indexes," IEEE Transactions on Knowledge and Data Engineering, vol. 18, no. 5, pp. 651-668, May 2006, doi:10.1109/TKDE.2006.81
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