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Conference Paper: Change tolerant indexing for constantly evolving data

TitleChange tolerant indexing for constantly evolving data
Authors
Issue Date2005
Citation
Proceedings - International Conference On Data Engineering, 2005, p. 391-402 How to Cite?
AbstractIndex structures are designed to optimize search performance, while at the same time supporting efficient data updates. Although not explicit, existing index structures are typically based upon the assumption that the rate of updates will be small compared to the rate of querying. This assumption is not valid in streaming data environments such as sensor and moving object databases, where updates are received incessantly. In fact, for many applications, the rate of updates may well exceed the rate of querying. In such environments, index structures suffer from poor performance due to the large overhead of keeping the index updated with the latest data. Recent efforts at indexing moving object data assume objects move in a restrictive manner (e.g. in straight lines with constant velocity). In this paper, we propose an index structure explicitly designed to perform well for both querying and updating. We assume a more relaxed model of object movement. In particular, we observe that objects often stay in a region (e.g., building) for an extended amount of time, and exploit this phenomenon to optimize an index for both updates and queries. The paper is developed with the example of R-trees, but the ideas can be extended to other index structures as well. We present the design of the Change Tolerant R-tree, and an experimental evaluation. © 2005 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/151874
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorCheng, Ren_US
dc.contributor.authorXia, Yen_US
dc.contributor.authorPrabhakar, Sen_US
dc.contributor.authorShah, Ren_US
dc.date.accessioned2012-06-26T06:30:17Z-
dc.date.available2012-06-26T06:30:17Z-
dc.date.issued2005en_US
dc.identifier.citationProceedings - International Conference On Data Engineering, 2005, p. 391-402en_US
dc.identifier.issn1084-4627en_US
dc.identifier.urihttp://hdl.handle.net/10722/151874-
dc.description.abstractIndex structures are designed to optimize search performance, while at the same time supporting efficient data updates. Although not explicit, existing index structures are typically based upon the assumption that the rate of updates will be small compared to the rate of querying. This assumption is not valid in streaming data environments such as sensor and moving object databases, where updates are received incessantly. In fact, for many applications, the rate of updates may well exceed the rate of querying. In such environments, index structures suffer from poor performance due to the large overhead of keeping the index updated with the latest data. Recent efforts at indexing moving object data assume objects move in a restrictive manner (e.g. in straight lines with constant velocity). In this paper, we propose an index structure explicitly designed to perform well for both querying and updating. We assume a more relaxed model of object movement. In particular, we observe that objects often stay in a region (e.g., building) for an extended amount of time, and exploit this phenomenon to optimize an index for both updates and queries. The paper is developed with the example of R-trees, but the ideas can be extended to other index structures as well. We present the design of the Change Tolerant R-tree, and an experimental evaluation. © 2005 IEEE.en_US
dc.languageengen_US
dc.relation.ispartofProceedings - International Conference on Data Engineeringen_US
dc.titleChange tolerant indexing for constantly evolving dataen_US
dc.typeConference_Paperen_US
dc.identifier.emailCheng, R:ckcheng@cs.hku.hken_US
dc.identifier.authorityCheng, R=rp00074en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/ICDE.2005.32en_US
dc.identifier.scopuseid_2-s2.0-28444485629en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-28444485629&selection=ref&src=s&origin=recordpageen_US
dc.identifier.spage391en_US
dc.identifier.epage402en_US
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridCheng, R=7201955416en_US
dc.identifier.scopusauthoridXia, Y=35319067700en_US
dc.identifier.scopusauthoridPrabhakar, S=7101672592en_US
dc.identifier.scopusauthoridShah, R=35365088300en_US
dc.identifier.citeulike4178312-

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