Synonyms
Spatiotemporal stream processing
Definition
A continuous spatial query runs over long periods of time and requests constant reporting of its result as the data dynamically change. Typically, the query type is range or nearest neighbor (NN), and the assumed distance metric is the Euclidean one. In general, there are multiple queries being processed simultaneously. The query points and the data objects move frequently and arbitrarily, i.e., their velocity vectors and motion patterns are unknown. They issue location updates to a central server, which processes them and continuously reports the current (i.e., updated) query results. Consider, for example, that the queries correspond to vacant cabs and that the data objects are pedestrians that ask for a taxi. As cabs and pedestrians move, each free taxi driver wishes to know his/her closest client. This is an instance of continuous NN monitoring. Spatial monitoring systems aim at minimizing the processing time at the server and/or...
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsRecommended Reading
Cai Y, Hua K, Cao G. Processing range-monitoring queries on heterogeneous mobile objects. In: Proceedings of the 5th IEEE International Conference on Mobile Data Management; 2004, p. 27–38.
Gedik B, Liu L. MobiEyes: distributed processing of continuously moving queries on moving objects in a mobile system. In: Advances in Database Technology, Proceedings of 9th International Conference on Extending Database Technology; 2004, p. 67–87.
Hu H, Xu J, Lee D. A generic framework for monitoring continuous spatial queries over moving objects. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2005, p. 479–90.
Kalashnikov D, Prabhakar S, Hambrusch S. Main memory evaluation of monitoring queries over moving objects. Distrib Parallel Databases. 2004;15(2):117–35.
Kang J, Mokbel M, Shekhar S, Xia T, Zhang D. Continuous evaluation of monochromatic and bichromatic reverse nearest neighbors. In: Proceedings of the 23rd International Conference on Data Engineering. 2007. p. 806–15.
Koudas N, Ooi B, Tan K, Zhang R. Approximate NN queries on streams with guaranteed error/performance bounds. In: Proceedings of the 30th International Conference on Very Large Data Bases. 2004. p. 804–15.
Mokbel M, Xiong X, Aref W. SINA: scalable incremental processing of continuous queries in spatio-temporal databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data. 2004. p. 623–34.
Mouratidis K, Bakiras S, Papadias D. Continuous monitoring of top-k queries over sliding windows. In: Proceedings of the ACM SIGMOD International Conference on Management of Data. 2006. p. 635–46.
Mouratidis K, Hadjieleftheriou M, Papadias D. Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring. In: Proceedings of the ACM SIGMOD International Conference on Management of Data. 2005. p. 634–45.
Mouratidis K, Papadias D. Continuous nearest neighbor queries over sliding windows. IEEE Trans Knowledge Data Eng. 2007;19(6):789–803.
Mouratidis K, Papadias D, Bakiras S, Tao Y. A threshold-based algorithm for continuous monitoring of k nearest neighbors. IEEE Trans Knowl Data Eng. 2005;17(11):1451–64.
Mouratidis K, Yiu M, Papadias D, Mamoulis N. Continuous nearest neighbor monitoring in road networks. In: Proceedings of the 32nd International Conference on Very Large Data Bases. 2006. p. 43–54.
Prabhakar S, Xia Y, Kalashnikov D, Aref W, Hambrusch S. Query indexing and velocity constrained indexing: scalable techniques for continuous queries on moving objects. IEEE Trans Comput. 2002;51(10):1124–40.
Tao Y, Papadias D. Maintaining sliding window skylines on data Streams. IEEE Trans Knowl Data Eng. 2006;18(3):377–91.
Xia T, Zhang D. Continuous reverse nearest neighbor monitoring. In: Proceedings of the 22nd International Conference on Data Engineering; 2006.
Xiong X, Mokbel M, Aref W. SEA-CNN: scalable processing of continuous k-nearest neighbor queries in spatio-temporal databases. In: Proceedings of the 21st International Conference on Data Engineering; 2005. p. 643–54.
Yu X, Pu K, Koudas N. Monitoring k-nearest neighbor queries over moving objects. In: Proceedings of the 21st International Conference on Data Engineering. 2005. p. 631–42.
Zhang D, Du Y, Hu L. On monitoring the top-k unsafe places. In: Proceedings of the 24th International Conference on Data Engineering; 2008. p. 337–45.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Mouratidis, K. (2018). Continuous Monitoring of Spatial Queries. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_82
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8265-9_82
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8266-6
Online ISBN: 978-1-4614-8265-9
eBook Packages: Computer ScienceReference Module Computer Science and Engineering