k-Nearest Neighbor Query Processing Algorithms for a Query Region in Road Networks

Recent development of wireless communication technologies and the popularity of smart phones .are making location-based services （LBS） popular. However, requesting queries to LBS servers with users＇ exact locations may threat the privacy of users. Therefore, there have been many researches on genera...

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Published in:	Journal of computer science and technology Vol. 28; no. 4; pp. 585 - 596
Main Authors:	Kim, Hyeong-Il, Chang, Jae-Woo
Format:	Journal Article
Language:	English
Published:	Boston Springer US 01.07.2013 Springer Nature B.V Cloud Open R&D Center, Chonbuk National University, Chonju 570-752, Korea Department of Computer Engineering, Chonbuk National University, Chonju 570-752, Korea%Department of Computer Engineering, Chonbuk National University, Chonju 570-752, Korea
Subjects:	Algorithms Analysis Artificial Intelligence Computer Science Data Structures and Information Theory Euclidean space Information Systems Applications (incl.Internet) Islands K-NN K-近邻算法 K近邻 Location based services Network management systems Networks Performance indices Privacy Queries Query processing Regular Paper Restaurants Roads Smartphones Software Engineering Studies Theory of Computation Wireless communication Wireless communications Wireless networks 基于位置的服务无线通信技术查询处理道路网络隐私保护 nearest neighbor query processing scheme road network island index location-based service k-nearest neighbor query processing scheme
ISSN:	1000-9000, 1860-4749
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Abstract	Recent development of wireless communication technologies and the popularity of smart phones .are making location-based services （LBS） popular. However, requesting queries to LBS servers with users＇ exact locations may threat the privacy of users. Therefore, there have been many researches on generating a cloaked query region for user privacy protection. Consequently, an efficient query processing algorithm for a query region is required. So, in this paper, we propose k-nearest neighbor query （k-NN） processing algorithms for a query region in road networks. To efficiently retrieve k-NN points of interest （POIs）, we make use of the Island index. We also propose a method that generates an adaptive Island index to improve the query processing performance and storage usage. Finally, we show by our performance analysis that our k-NN query processing algorithms outperform the existing k-Range Nearest Neighbor （kRNN） algorithm in terms of network expansion cost and query processing time.
AbstractList	Recent development of wireless communication technologies and the popularity of smart phones are making location-based services (LBS) popular. However, requesting queries to LBS servers with users’ exact locations may threat the privacy of users. Therefore, there have been many researches on generating a cloaked query region for user privacy protection. Consequently, an efficient query processing algorithm for a query region is required. So, in this paper, we propose k -nearest neighbor query ( k -NN) processing algorithms for a query region in road networks. To efficiently retrieve k -NN points of interest (POIs), we make use of the Island index. We also propose a method that generates an adaptive Island index to improve the query processing performance and storage usage. Finally, we show by our performance analysis that our k -NN query processing algorithms outperform the existing k -Range Nearest Neighbor ( k RNN) algorithm in terms of network expansion cost and query processing time. Recent development of wireless communication technologies and the popularity of smart phones are making location-based services (LBS) popular. However, requesting queries to LBS servers with users' exact locations may threat the privacy of users. Therefore, there have been many researches on generating a cloaked query region for user privacy protection. Consequently, an efficient query processing algorithm for a query region is required. So, in this paper, we propose k-nearest neighbor query (k-NN) processing algorithms for a query region in road networks. To efficiently retrieve k-NN points of interest (POIs), we make use of the Island index. We also propose a method that generates an adaptive Island index to improve the query processing performance and storage usage. Finally, we show by our performance analysis that our k-NN query processing algorithms outperform the existing k-Range Nearest Neighbor (kRNN) algorithm in terms of network expansion cost and query processing time.[PUBLICATION ABSTRACT] Recent development of wireless communication technologies and the popularity of smart phones are making location-based services (LBS) popular. However, requesting queries to LBS servers with users' exact locations may threat the privacy of users. Therefore, there have been many researches on generating a cloaked query region for user privacy protection. Consequently, an efficient query processing algorithm for a query region is required. So, in this paper, we propose k-nearest neighbor query (k-NN) processing algorithms for a query region in road networks. To efficiently retrieve k-NN points of interest (POIs), we make use of the Island index. We also propose a method that generates an adaptive Island index to improve the query processing performance and storage usage. Finally, we show by our performance analysis that our k-NN query processing algorithms outperform the existing k-Range Nearest Neighbor (kRNN) algorithm in terms of network expansion cost and query processing time. Recent development of wireless communication technologies and the popularity of smart phones .are making location-based services （LBS） popular. However, requesting queries to LBS servers with users＇ exact locations may threat the privacy of users. Therefore, there have been many researches on generating a cloaked query region for user privacy protection. Consequently, an efficient query processing algorithm for a query region is required. So, in this paper, we propose k-nearest neighbor query （k-NN） processing algorithms for a query region in road networks. To efficiently retrieve k-NN points of interest （POIs）, we make use of the Island index. We also propose a method that generates an adaptive Island index to improve the query processing performance and storage usage. Finally, we show by our performance analysis that our k-NN query processing algorithms outperform the existing k-Range Nearest Neighbor （kRNN） algorithm in terms of network expansion cost and query processing time.
Author	Hyeong-Il Kim Jae-Woo Chang
AuthorAffiliation	Department of Computer Engineering, Chonbuk National University, Chonju 570-752, Korea Cloud Open R＆D Center, Chonbuk National University, Chonju 570-752, Korea
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Cites_doi	10.1023/A:1015231126594 10.1109/TKDE.2007.190662 10.1016/j.sysarc.2012.05.003 10.1109/MSPEC.2003.1209608 10.1109/MSPEC.2006.1652998 10.1007/s11277-008-9608-9 10.1109/TPDS.2009.65 10.1109/CIT.2011.87 10.1145/2245276.2245379 10.1007/978-3-642-02982-0_19 10.1109/MDM.2010.40 10.1007/978-3-540-73540-3_13 10.1007/11535331_5
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Copyright	Springer Science+Business Media New York & Science Press, China 2013 Springer Science+Business Media New York & Science Press, China 2013. Copyright © Wanfang Data Co. Ltd. All Rights Reserved.
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Notes	11-2296/TP Recent development of wireless communication technologies and the popularity of smart phones .are making location-based services （LBS） popular. However, requesting queries to LBS servers with users＇ exact locations may threat the privacy of users. Therefore, there have been many researches on generating a cloaked query region for user privacy protection. Consequently, an efficient query processing algorithm for a query region is required. So, in this paper, we propose k-nearest neighbor query （k-NN） processing algorithms for a query region in road networks. To efficiently retrieve k-NN points of interest （POIs）, we make use of the Island index. We also propose a method that generates an adaptive Island index to improve the query processing performance and storage usage. Finally, we show by our performance analysis that our k-NN query processing algorithms outperform the existing k-Range Nearest Neighbor （kRNN） algorithm in terms of network expansion cost and query processing time. Hyeong-Il Kim and Jae-Woo Chang（ 1 Department of Computer Engineering, Chonbuk National University, Chonju 570-752, Korea 2 Cloud Open R＆D Center, Chonbuk National University, Chonju 570-752, Korea E-mail： {melipion, jwchang}@jbnu.ac.kr ） island index, k-nearest neighbor query processing scheme, locatiombased service, road network ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23
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Publisher	Springer US Springer Nature B.V Cloud Open R&D Center, Chonbuk National University, Chonju 570-752, Korea Department of Computer Engineering, Chonbuk National University, Chonju 570-752, Korea%Department of Computer Engineering, Chonbuk National University, Chonju 570-752, Korea
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Snippet	Recent development of wireless communication technologies and the popularity of smart phones .are making location-based services （LBS） popular. However,... Recent development of wireless communication technologies and the popularity of smart phones are making location-based services (LBS) popular. However,...
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SubjectTerms	Algorithms Analysis Artificial Intelligence Computer Science Data Structures and Information Theory Euclidean space Information Systems Applications (incl.Internet) Islands K-NN K-近邻算法 K近邻 Location based services Network management systems Networks Performance indices Privacy Queries Query processing Regular Paper Restaurants Roads Smartphones Software Engineering Studies Theory of Computation Wireless communication Wireless communications Wireless networks 基于位置的服务无线通信技术查询处理道路网络隐私保护
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Title	k-Nearest Neighbor Query Processing Algorithms for a Query Region in Road Networks
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