Please use this identifier to cite or link to this item: https://doi.org/10.1145/1376616.1376622
DC FieldValue
dc.titleST2B-tree: A self-tunable spatio-temporal B+-tree index for moving objects
dc.contributor.authorChen, S.
dc.contributor.authorOoi, B.C.
dc.contributor.authorTan, K.-L.
dc.contributor.authorNascimento, M.A.
dc.date.accessioned2013-07-04T08:03:59Z
dc.date.available2013-07-04T08:03:59Z
dc.date.issued2008
dc.identifier.citationChen, S.,Ooi, B.C.,Tan, K.-L.,Nascimento, M.A. (2008). ST2B-tree: A self-tunable spatio-temporal B+-tree index for moving objects. Proceedings of the ACM SIGMOD International Conference on Management of Data : 29-42. ScholarBank@NUS Repository. <a href="https://doi.org/10.1145/1376616.1376622" target="_blank">https://doi.org/10.1145/1376616.1376622</a>
dc.identifier.isbn9781605581026
dc.identifier.issn07308078
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40424
dc.description.abstractIn a moving objects database (MOD) the dataset and the workload change frequently. As the locations of objects change in space and time, the data distribution also changes and the answer for a same query over the same region may vary widely over time. As a result, traditional static indexes are not able to perform well and it is critical to develop self-tuning indexes that can be reconfigured automatically based on the state of the system. Towards this goal we propose the ST2B-tree, a Self- Tunable Spatio- Temporal B +-Tree index for MODs, which is amenable to tuning. Frequent updates to its subtrees allows rebuilding (tuning) a subtree using a different set of reference points and different grid size without significant overhead. We also present an online tuning framework for the ST2B-tree, where the tuning is conducted online and automatically without human intervention, also not interfering with regular functions of the MOD. Our extensive experiments show that the self-tuning process minimizes the effectiveness degradation of the index caused by workload changes at the cost of virtually no overhead. Copyright 2008 ACM.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1145/1376616.1376622
dc.sourceScopus
dc.subjectData distribution
dc.subjectIndex tuning
dc.subjectLocation-based services
dc.subjectMoving object indexing
dc.subjectSelf-tuning
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1145/1376616.1376622
dc.description.sourcetitleProceedings of the ACM SIGMOD International Conference on Management of Data
dc.description.page29-42
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

62
checked on May 14, 2019

Page view(s)

66
checked on May 17, 2019

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.