Continuous possible K-nearest skyline query in euclidean spaces

Yuan Ko Huang, Zong Han He, Chiang Lee, Wu Hsiu Kuo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Continuous K-nearest skyline query (CKNSQ) is an important type of the spatio-temporal queries. Given a query time interval [ts, te] and a moving query object q, a CKNSQ is to retrieve the K-nearest skyline points of q at each time instant within [ts, te]. Different from the previous works, our work devotes to overcoming the past assumption that each object is static with certain dimensional values and located in road networks. In this paper, we focus on processing the CKNSQ over moving objects with uncertain dimensional values in Euclidean space and the velocity of each object (including the query object) varies within a known range. Such a query is called the continuous possible K-nearest skyline query (CPKNSQ). We first discuss the difficulties raised by the uncertainty of object and then propose the CPKNSQ algorithm operated with a data partitioning index, called the uncertain TPR-tree (UTPR-tree), to efficiently answer the CPKNSQ.

Original languageEnglish
Title of host publicationProceedings - 2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013
PublisherIEEE Computer Society
Pages174-181
Number of pages8
ISBN (Print)9781479920815
DOIs
Publication statusPublished - 2013 Jan 1
Event2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013 - Seoul, Korea, Republic of
Duration: 2013 Dec 152013 Dec 18

Publication series

NameProceedings of the International Conference on Parallel and Distributed Systems - ICPADS
ISSN (Print)1521-9097

Other

Other2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013
CountryKorea, Republic of
CitySeoul
Period13-12-1513-12-18

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture

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