In this chapter, we deal with trajectory database management issues and physical aspects of trajectory database systems, such as indexing and query processing. Our emphasis is on historical databases handling past positions of moving objects represented as trajectories. This is because only such databases can be used in the context of trajectory data warehouses, which is the core subject of this book.
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References
S. Acharya, V. Poosala, and S. Ramaswamy. Selectivity estimation in spatial databases. In Proceedings of the International Conference on Management of Data (SIGMOD ’99), pp. 13–24, 1999.
V.T. Almeida and R.H. Güting. Indexing the trajectories of moving objects in networks. GeoInformatica, 9(1):33–60, 2005.
V.T. Almeida, R.H. Güting, and T. Behr. Querying moving objects in secondo. In Proceedings of Seventh International Conference on Mobile Data Management (MDM ’06), p. 47, 2006.
S. Arumugam and C. Jermaine. Closest-point-of-approach join for moving object histories. In Proceedings of the 22th International Conference on Data Engineering (ICDE’06), p. 86, 2006.
P. Bakalov, M. Hadjieleftheriou, E.J. Keogh, and V.J. Tsotras. Efficient trajectory joins using symbolic representations. In Proceedings Sixth International Conference on Mobile Data Management (MDM’05), pp. 86–93, 2005.
P. Bakalov, M. Hadjieleftheriou, and V.J. Tsotras. Time relaxed spatiotemporal trajectory joins. In Proceedings of the 13th annual ACM international workshop on Geographic Information Systems (GIS’05), pp. 182–191, 2005.
R. Benetis, C.S. Jensen, G. Karciauskas, and S. Saltenis. Nearest neighbor and reverse nearest neighbor queries for moving objects. In Proceedings of the International Symposium on Database Engineering and Applications (IDEAS’02), pp. 44–53, 2002.
D.J. Berndt and J. Clifford. Finding patterns in time series: A dynamic programming approach. In Advances in Knowledge Discovery and Data Mining, pp. 229–248. MIT Press, 1996.
S. Brakatsoulas, D. Pfoser, R. Salas, and C. Wenk. On map-matching vehicle tracking data. In Proceeding on 31st International Conference on Very Large Data Bases (VLDB’05), pp. 853–864, 2005.
H. Cao, O. Wolfson, and G. Trajcevski. Spatio-temporal data reduction with deterministic error bounds. In Proceedings of Discrete Algorithms and Methods for Mobile Computing and Communications-Principles of Mobile Computing (DIALM-POMC’03), pp. 33–42, 2003.
V.P. Chakka, A. Everspaugh, and J.M. Patel. Indexing large trajectory data sets with SETI. In Proceedings of Conference on Innovative Data Systems Research (CIDR’03), 2003.
L. Chen, M.T. Özsu, and V. Oria. Robust and fast similarity search for moving object trajectories. In Proceedings of the International Conference on Management of Data (SIGMOD’05), pp. 491–502, 2005.
R. Cheng, D.V. Kalashnikov, and S. Prabhakar. Evaluating probabilistic queries over imprecise data. In Proceedings of the International Conference on Management of Data (SIGMOD’03), pp. 551–562, 2003.
K.L. Cheung and A.W.-C. Fu. Enhanced nearest neighbour search on the R-tree. SIGMOD Record, 27(3):16–21, 1998.
Y.-J. Choi and C.-W. Chung. Selectivity estimation for spatio-temporal queries to moving objects. In Proceedings of the International Conference on Management of Data (SIGMOD’02), pp. 440–451, 2002.
A. Civilis, C.S. Jensen, J. Nenortaite, and S. Pakalnis. Efficient tracking of moving objects with precision guarantees. In Proceedings of The Annual International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous’04), pp. 164–173, 2004.
S. Dieker and R.H. Güting. Plug and play with query algebras: SECONDO-a generic dbms development environment. In Proceedings of the International Symposium on Database Engineering and Applications (IDEAS’00), pp. 380–392, 2000.
D. Douglas and T. Peucker. Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. The Canadian Cartographer, 10(2):112–122, 1973.
L. Forlizzi, R.H. Güting, E. Nardelli, and M. Schneider. A data model and data structures for moving objects databases. In Proceedings of the International Conference on Management of Data (SIGMOD’00), pp. 319–330, 2000.
E. Frentzos. Indexing objects moving on fixed networks. In Proceedings of the 7th International Symposium on Spatial and Temporal Databases (SSTD’03), pp. 289–305, 2003.
E. Frentzos, K. Gratsias, N. Pelekis, and Y. Theodoridis. Algorithms for nearest neighbor search on moving object trajectories. Geoinformatica, 11(2):159–193, 2007.
E. Frentzos, K. Gratsias, and Y. Theodoridis. Index-based most similar search. In Proceedings of the 23th International Conference on Data Engineering (ICDE’07), 2007.
J. Greenfeld. Matching gps observations to locations on a digital map. In 81th Annual Meeting of the Transportation Research Board, pp. 164–173, 2004.
R.H. Güting and M. Schneider. Realm-based spatial data types: The rose algebra. Very Large Data Bases Journal, 4:243–286, 1995.
R.H. Güting, M.H. Böhlen, M. Erwig, C.S. Jensen, N.A. Lorentzos, M. Schneider, and M. Vazirgiannis. A foundation for representing and quering moving objects. ACM Transactions Database Systems, 25(1):1–42, 2000.
R. Güting, T. Behr, V. Almeida, Z. Ding, F. Hoffmann, and M. Spiekermann. SECONDO: An extensible dbms architecture and prototype. fernuniversitat hagen, informatik-report 313, 2004.
A. Guttman. R-trees: A dynamic index structure for spatial searching. In Proceedings of the International Conference on Management of Data (SIGMOD’84), pp. 47–57, 1984.
M. Hadjieleftheriou, G. Kollios, V.J. Tsotras, and D. Gunopulos. Efficient indexing of spatiotemporal objects. In Proceedings of Seventh International Conference on Extending Database Technology (EDBT’02), pp. 251–268, 2002.
M. Hadjieleftheriou, G. Kollios, and V.J. Tsotras. Performance evaluation of spatio-temporal selectivity estimation techniques. In Proceedings of 15th International Conference on Scientific and Statistical Database Management (SSDBM’03), pp. 202–211, 2003.
M. Hadjieleftheriou, G. Kollios, V.J. Tsotras, and D. Gunopulos. Indexing spatio-temporal archives. Very Large Data Bases Journal, 15(2):143–164, 2006.
G.R. Hjaltason and H. Samet. Distance browsing in spatial databases. ACM Transactions Database Systems, 24(2):265–318, 1999.
Y.-W. Huang, N. Jing, and E.A. Rundensteiner. Spatial joins using R-trees: Breadth-first traversal with global optimizations. The Very Large Data Bases Journal, 396–405, 1997.
G.S. Iwerks, H. Samet, and K. Smith. Continuous k-nearest neighbor queries for continuously moving points with updates. In Proceeding on 29th International Conference on Very Large Data Bases (VLDB’03), pp. 512–523, 2003.
J.A.C. Lema, L. Forlizzi, R.H. Güting, E. Nardelli, and M. Schneider. Algorithms for moving objects databases. The Computer Journal, 46(6):680–712, 2003.
Y. Manolopoulos, A. Nanopoulos, A. Papadopoulos, and Y. Theodoridis. Rtrees: Theory and Applications. Springer, Berlin Heidelberg New York, 2005.
N. Meratnia and R.A. de By. Spatiotemporal compression techniques for moving point objects. In Nineth International Conference on Extending Database Technology (EDBT’04), pp. 765–782, 2004.
K. Mouratidis, D. Papadias, and M. Hadjieleftheriou. Conceptual partitioning: An efficient method for continuous nearest neighbor monitoring. In Proceedings of the International Conference on Management of Data(SIGMOD’05), pp. 634–645, 2005.
M. Nanni. Clustering Methods for Spatio-Temporal Data. Ph.D. thesis, Computer Science Department, University of Pisa, 2002.
Oracle ®;database documentation library, 10g release 1 (10.1), 2006.
J. O’Rourke. Computational Geometry in C. Cambridge University Press, Camridge (NY), 1998.
T. Palpanas, M. Vlachos, E.J. Keogh, D. Gunopulos, and W. Truppel. Online amnesic approximation of streaming time series. In Proceedings of the 20th International Conference on Data Engineering, pp. 338–349, 2004.
N. Pelekis. STAU: A spatio-temporal extension to ORACLE DBMS, Ph.D., UMIST. Ph.D. thesis, 2002.
N. Pelekis and Y. Theodoridis. Boosting location-based services with a moving object database engine. In Proceedings of Workshop on Data Engineering for Wireless and Mobile Access (MobiDE’06), pp. 3–10, 2006.
N. Pelekis, Y. Theodoridis, S. Vosinakis, and T. Panayiotopoulos. Hermes – a framework for location-based data management. In 11th International Conference on Extending Database Technology (EDBT’06), pp. 1130–1134, 2006.
N. Pelekis, B. Theodoulidis, Y. Theodoridis, and I. Kopanakis. An Oracle data cartridge for moving objects. Technical report, University of Piraeus, 2005.
D. Pfoser and C.S. Jensen. Capturing the uncertainty of moving-object representations. In Proceedings of Symposium on Advances in Spatial Databases (SSD’99), pp. 111–132, 1999.
D. Pfoser and C.S. Jensen. Querying the trajectories of on-line mobile objects. In Proceedings of Workshop on Data Engineering for Wireless and Mobile Access (MobiDE’01), pp. 66–73, 2001.
D. Pfoser and C.S. Jensen. Indexing of network constrained moving objects. In Proceedings of the 11th Annual ACM International Workshop on Geographic Information Systems (GIS’03), pp. 25–32, 2003.
D. Pfoser, C.S. Jensen, and Y. Theodoridis. Novel approaches in query processing for moving object trajectories. In Proceeding on 26th International Conference on Very Large Data Bases (VLDB’00), pp. 395–406, 2000.
M. Potamias, K. Patroumpas, and T.K. Sellis. Amnesic online synopses for moving objects. In Proceedings of Conference on Information and Knowledge Management (CIKM’06), 2006.
M. Potamias, K. Patroumpas, and T.K. Sellis. Sampling trajectory streams with spatiotemporal criteria. In Proceedings of 18th International Conference on Scientific and Statistical Database Management (SSDBM’06), pp. 275–284, 2006.
C.M. Procopiuc, P.K. Agarwal, and S. Har-Peled. Star-tree: An efficient self-adjusting index for moving objects. In Proceedings of the Fourth Workshop on Algorithm Engineering and Experiments (ALENEX’02), pp. 178–193, 2002.
S. Rasetic, J. Sander, J. Elding, and M.A. Nascimento. A trajectory splitting model for efficient spatio-temporal indexing. In Proceeding on 31st International Conference on Very Large Data Bases (VLDB’05), pp. 934–945, 2005.
N. Roussopoulos, S. Kelley, and F. Vincent. Nearest neighbor queries. In Proceedings of the International Conference on Management of Data (SIGMOD’95), pp. 71–79, 1995.
S. Saltenis and C.S. Jensen. Indexing of moving objects for location-based services. In Proceedings of the 18th International Conference on Data Engineering, pp. 463–472, 2002.
S. Saltenis, C.S. Jensen, S.T. Leutenegger, and M.A. Lopez. Indexing the positions of continuously moving objects. In Proceedings of the International Conference on Management of Data (SIGMOD’00), pp. 331–342, 2000.
Z. Song and N. Roussopoulos. K-nearest neighbor search for moving query point. In Proceedings of the Fourth International Symposium on Spatial and Temporal Databases, pp. 79–96, 2001.
Y. Tao and D. Papadias. Time-parameterized queries in spatio-temporal databases. In Proceedings of the International Conference on Management of Data (SIGMOD’02), pp. 334–345, 2002.
Y. Tao and D. Papadias. Performance analysis of R*-trees with arbitrary node extents. IEEE Transactions on Knowledge and Data Engeneering, 16(6):653–668, 2004.
Y. Tao, D. Papadias, and Q. Shen. Continuous nearest neighbor search. In Proceeding on 28th International Conference on Very Large Data Bases (VLDB’02), pp. 287–298, 2002.
Y. Tao, J. Sun, and D. Papadias. Selectivity estimation for predictive spatio-temporal queries. In Proceedings of the 19th International Conference on Data Engineering (ICDE ’03), pp. 417–428, 2003.
Y. Tao, D. Papadias, and J. Sun. The TPR*-tree: An optimized spatio-temporal access method for predictive queries. In Proceeding on 29th International Conference on Very Large Data Bases (VLDB’03), pp. 790–801, 2003.
Y. Tao, G. Kollios, J. Considine, F. Li, and D. Papadias. Spatio-temporal aggregation using sketches. In Proceedings of the 20th International Conference on Data Engineering, pp. 214–226, 2004.
Y. Theodoridis. Ten benchmark database queries for location-based services. The Computer Journal, 46(6):713–725, 2003.
Y. Theodoridis and T.K. Sellis. A model for the prediction of R-tree performance. In Proceedings of Symposium on Principles of Database Systems (PODS’96), pp. 161–171, 1996.
Y. Theodoridis, M. Vazirgiannis, and T.K. Sellis. Spatio-temporal indexing for large multimedia applications. In Proceedings of IEEE International Conference on Multimedia Computing and Systems (ICMCS’96), pp. 441–448, 1996.
Y. Theodoridis, E. Stefanakis, and T.K. Sellis. Cost models for join queries in spatial databases. In Proceedings of the 14th International Conference on Data Engineering (ICDE ’98), pp. 476–483, 1998.
G. Trajcevski. Probabilistic range queries in moving objects databases with uncertainty. In Proceedings of Workshop on Data Engineering for Wireless and Mobile Access (MobiDE’03), pp. 39–45, 2003.
G. Trajcevski, O. Wolfson, K. Hinrichs, and S. Chamberlain. Managing uncertainty in moving objects databases. ACM Transactions on Database System, 29(3):463–507, 2004.
M. Vlachos, G. Kollios, and D. Gunopulos. Discovering similar multidimensional trajectories. In Proceedings of the 18th International Conference on Data Engineering (ICDE ’02), pp. 673–684, 2002.
C. Wenk, R. Salas, and D. Pfoser. Addressing the need for map-matching speed: Localizing globalb curve-matching algorithms. In Proceedings of 18th International Conference on Scientific and Statistical Database Management (SSDBM’06), pp. 379–388, 2006.
O. Wolfson, A.P. Sistla, S. Chamberlain, and Y. Yesha. Updating and querying databases that track mobile units. Distributed and Parallel Databases, 7(3):257–387, 1999.
M. Worboys and M. Duckham. GIS: A Computing Perspective, 2nd edn. CRC Press, Florida, 2004.
Y. Xia and S. Prabhakar. Q+rtree: Efficient indexing for moving object database. In Proceedings of The Eighth International Conference on Database Systems for Advanced Applications (DASFAA’03), pp. 175–182, 2003.
X. Xiong, M.F. Mokbel, and W.G. Aref. Sea-cnn: Scalable processing of continuous k-nearest neighbor queries in spatio-temporal databases. In Proceedings of the 21th International Conference on Data Engineering (ICDE ’05), pp. 643–654, 2005.
H. Yin and O. Wolfson. A weight-based map matching method in moving objects databases. In Proceedings of 16th International Conference on Scientific and Statistical Database Management (SSDBM’04), pp. 437–438, 2004.
X. Yu, K.Q. Pu, and N. Koudas. Monitoring k-nearest neighbor queries over moving objects. In Proceedings of the 21th International Conference on Data Engineering (ICDE ’05), pp. 631–642, 2005.
H. Zhu, J. Su, and O.H. Ibarra. Trajectory queries and octagons in moving object databases. In Proceedings of Conference on Information and Knowledge Management (CIKM’02), pp. 413–421, 2002.
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Frentzos, E., Pelekis, N., Ntoutsi, I., Theodoridis, Y. (2008). Trajectory Database Systems. In: Giannotti, F., Pedreschi, D. (eds) Mobility, Data Mining and Privacy. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75177-9_7
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