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

Fingerprint

Processing
Uncertainty

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture

Cite this

Huang, Y. K., He, Z. H., Lee, C., & Kuo, W. H. (2013). Continuous possible K-nearest skyline query in euclidean spaces. In Proceedings - 2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013 (pp. 174-181). [6808172] (Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS). IEEE Computer Society. https://doi.org/10.1109/ICPADS.2013.35
Huang, Yuan Ko ; He, Zong Han ; Lee, Chiang ; Kuo, Wu Hsiu. / Continuous possible K-nearest skyline query in euclidean spaces. Proceedings - 2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013. IEEE Computer Society, 2013. pp. 174-181 (Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS).
@inproceedings{ee5eb3aded114003a5d84b860ad51801,
title = "Continuous possible K-nearest skyline query in euclidean spaces",
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.",
author = "Huang, {Yuan Ko} and He, {Zong Han} and Chiang Lee and Kuo, {Wu Hsiu}",
year = "2013",
month = "1",
day = "1",
doi = "10.1109/ICPADS.2013.35",
language = "English",
isbn = "9781479920815",
series = "Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS",
publisher = "IEEE Computer Society",
pages = "174--181",
booktitle = "Proceedings - 2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013",
address = "United States",

}

Huang, YK, He, ZH, Lee, C & Kuo, WH 2013, Continuous possible K-nearest skyline query in euclidean spaces. in Proceedings - 2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013., 6808172, Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS, IEEE Computer Society, pp. 174-181, 2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013, Seoul, Korea, Republic of, 13-12-15. https://doi.org/10.1109/ICPADS.2013.35

Continuous possible K-nearest skyline query in euclidean spaces. / Huang, Yuan Ko; He, Zong Han; Lee, Chiang; Kuo, Wu Hsiu.

Proceedings - 2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013. IEEE Computer Society, 2013. p. 174-181 6808172 (Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS).

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

TY - GEN

T1 - Continuous possible K-nearest skyline query in euclidean spaces

AU - Huang, Yuan Ko

AU - He, Zong Han

AU - Lee, Chiang

AU - Kuo, Wu Hsiu

PY - 2013/1/1

Y1 - 2013/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84900864332&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84900864332&partnerID=8YFLogxK

U2 - 10.1109/ICPADS.2013.35

DO - 10.1109/ICPADS.2013.35

M3 - Conference contribution

AN - SCOPUS:84900864332

SN - 9781479920815

T3 - Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS

SP - 174

EP - 181

BT - Proceedings - 2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013

PB - IEEE Computer Society

ER -

Huang YK, He ZH, Lee C, Kuo WH. Continuous possible K-nearest skyline query in euclidean spaces. In Proceedings - 2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013. IEEE Computer Society. 2013. p. 174-181. 6808172. (Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS). https://doi.org/10.1109/ICPADS.2013.35