A collaborative approach to moving k-nearest neighbor queries in directed and dynamic road networks

被引:4
|
作者
Cho, Hyung-Ju [1 ]
Jin, Rize [2 ]
Chung, Tae-Sun [2 ]
机构
[1] Kyungpook Natl Univ, Sch Comp Informat, Sangju Si 742711, Gyeongsangbuk D, South Korea
[2] Ajou Univ, Dept Informat & Comp Engn, Suwon 443749, Gyeonggi Do, South Korea
基金
新加坡国家研究基金会;
关键词
Directed and dynamic road network; Moving k-nearest neighbor query; Safe segment; Influence region; SEARCH;
D O I
10.1016/j.pmcj.2014.07.002
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we investigate a new approach to moving k-nearest neighbor (MkNN) queries in directed and dynamic road networks, where each road segment has a particular orientation and its travel time changes depending on traffic conditions. An MkNN query continuously finds the k nearest neighbors (NNs) of a moving query object. Most existing studies have focused on MkNN queries in undirected and static road networks, where each road segment is bidirectional and its travel time does not change over time. However, little attention has been paid to MkNN queries in directed and dynamic road networks. In this research, we propose COMET, a collaborative approach to Moving k nEaresT neighbor queries in directed and dynamic road networks, where query processing is performed through collaboration between the server and query objects. In addition, we conduct extensive experiments to show that COMET substantially outperforms a conventional method in terms of query response time, bandwidth usage, and energy consumption. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:139 / 156
页数:18
相关论文
共 50 条
  • [31] K-nearest neighbor skyline queries in mobile environment
    Nie, Jing, 1600, Transport and Telecommunication Institute, Lomonosova street 1, Riga, LV-1019, Latvia (18):
  • [32] Continuous range k-nearest neighbor queries in vehicular ad hoc networks
    Cho, Hyung-Ju
    JOURNAL OF SYSTEMS AND SOFTWARE, 2013, 86 (05) : 1323 - 1332
  • [33] Reverse k Nearest Neighbor Queries in Time-Dependent Road Networks
    Li, Jiajia
    Li, Yuxian
    Shen, Panpan
    Xia, Xiufeng
    Zong, Chuanyu
    Xia, Chenxi
    IEEE 20TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS / IEEE 16TH INTERNATIONAL CONFERENCE ON SMART CITY / IEEE 4TH INTERNATIONAL CONFERENCE ON DATA SCIENCE AND SYSTEMS (HPCC/SMARTCITY/DSS), 2018, : 1064 - 1069
  • [34] Efficient reverse spatial and textual k nearest neighbor queries on road networks
    Luo, Changyin
    Li Junlin
    Li, Guohui
    Wei, Wei
    Li, Yanhong
    Li, Jianjun
    KNOWLEDGE-BASED SYSTEMS, 2016, 93 : 121 - 134
  • [35] An Approximate Indexing Method for Efficient Processing of k-Nearest Neighbor Queries in Road Network Environment
    Lee, Sang-Chul
    Kim, Sang-Wook
    Lee, Junghoon
    Yoo, Jae Soo
    INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL, 2011, 14 (04): : 1247 - 1264
  • [36] K-Nearest Neighbor Particle Filters for Dynamic Hybrid Bayesian Networks
    Chen, Hongda
    Chang, K. C.
    IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2008, 44 (03) : 1091 - 1101
  • [37] Continue reverse nearest neighbor queries in road networks
    Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China
    Shenyang Jianzhu Daxue Xuebao (Ziran Kexue Ban)/Journal of Shenyang Jianzhu University (Natural Science), 2007, 23 (04): : 688 - 692
  • [38] Flexible Aggregate Nearest Neighbor Queries in Road Networks
    Yao, Bin
    Chen, Zhongpu
    Gao, Xiaofeng
    Shang, Shuo
    Ma, Shuai
    Guo, Minyi
    2018 IEEE 34TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 2018, : 761 - 772
  • [39] A Road Network Embedding Technique for K-Nearest Neighbor Search in Moving Object Databases
    Cyrus Shahabi
    Mohammad R. Kolahdouzan
    Mehdi Sharifzadeh
    GeoInformatica, 2003, 7 : 255 - 273
  • [40] Aggregate keyword nearest neighbor queries on road networks
    Zhang, Pengfei
    Lin, Huaizhong
    Gao, Yunjun
    Lu, Dongming
    GEOINFORMATICA, 2018, 22 (02) : 237 - 268