(A)kNN Query Processing on the Cloud: A Survey

被引:4
|
作者
Nodarakis, Nikolaos [1 ]
Rapti, Angeliki [1 ]
Sioutas, Spyros [2 ]
Tsakalidis, Athanasios K. [1 ]
Tsolis, Dimitrios [3 ]
Tzimas, Giannis [4 ]
Panagis, Yannis [5 ]
机构
[1] Univ Patras, Comp Engn & Informat Dept, Patras 26504, Greece
[2] Ionian Univ, Dept Informat, Corfu 49100, Greece
[3] Univ Patras, Dept Cultural Heritage Management & New Technol, Patras 26504, Greece
[4] Inst Western Greece, Comp & Informat Engn Dept, Technol Educ, Patras 26334, Greece
[5] Univ Copenhagen, Ctr Excellence Int Courts, DK-1455 Copenhagen, Denmark
关键词
Big data; Nearest neighbor; MapReduce; NoSQL; Query processing; SPATIAL DATA; NEIGHBOR; SYSTEM; HADOOP;
D O I
10.1007/978-3-319-57045-7_3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A k-nearest neighbor (kNN) query determines the k nearest points, using distance metrics, from a given location. An all k-nearest neighbor (AkNN) query constitutes a variation of a kNN query and retrieves the k nearest points for each point inside a database. Their main usage resonates in spatial databases and they consist the backbone of many location-based applications and not only. Although (A) kNN is a fundamental query type, it is computationally very expensive. During the last years a multiplicity of research papers has focused around the distributed (A) kNN query processing on the cloud. This work constitutes a survey of research efforts towards this direction. The main contribution of this work is an up-to-date review of the latest (A) kNN query processing approaches. Finally, we discuss various research challenges and directions of further research around this domain.
引用
收藏
页码:26 / 40
页数:15
相关论文
共 50 条
  • [41] Fast kNN query processing over a multi-node GPU environment
    Ricardo J. Barrientos
    Javier A. Riquelme
    Ruber Hernández-García
    Cristóbal A. Navarro
    Wladimir Soto-Silva
    The Journal of Supercomputing, 2022, 78 : 3045 - 3071
  • [42] Distributed kNN Query Authentication
    Zhang, Ce
    Xu, Cheng
    Xu, Jianliang
    Choi, Byron
    2018 19TH IEEE INTERNATIONAL CONFERENCE ON MOBILE DATA MANAGEMENT (MDM 2018), 2018, : 167 - 176
  • [43] Dynamic spatial index for efficient query processing on the cloud
    Ibrahim Kamel
    Ayesha M. Talha
    Zaher Al Aghbari
    Journal of Cloud Computing, 6
  • [44] Facilitating Secure and Efficient Spatial Query Processing on the Cloud
    Talha, Ayesha
    Kamel, Ibrahim
    Al Aghbari, Zaher
    IEEE TRANSACTIONS ON CLOUD COMPUTING, 2019, 7 (04) : 988 - 1001
  • [45] The String Similarity Query Processing in Cloud Computing System
    LiaoYuanLai
    INTERNATIONAL JOURNAL OF GRID AND DISTRIBUTED COMPUTING, 2015, 8 (02): : 25 - 35
  • [46] An efficient query processing optimization based on ELM in the cloud
    Linlin Ding
    Junchang Xin
    Guoren Wang
    Neural Computing and Applications, 2016, 27 : 35 - 44
  • [47] Non-Intrusive Elastic Query Processing in the Cloud
    Ticiana L.Coelho da Silva
    Mario A.Nascimento
    Jos Antnio F.de Macêdo
    Fl′avio R.C.Sousa
    Javam C.Machado
    Journal of Computer Science & Technology, 2013, 28 (06) : 932 - 947
  • [48] Dynamic spatial index for efficient query processing on the cloud
    Kamel, Ibrahim
    Talha, Ayesha M.
    Al Aghbari, Zaher
    JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS, 2017, 6
  • [49] Secure query processing and optimization in cloud environment: a review
    Divya, V. L.
    Job, P. A.
    Preetha, Mathew K.
    INFORMATION SECURITY JOURNAL, 2024, 33 (02): : 172 - 191
  • [50] Non-Intrusive Elastic Query Processing in the Cloud
    Ticiana L. Coelho da Silva
    Mario A. Nascimento
    José Antônio F. de Macêdo
    Flávio R. C. Sousa
    Javam C. Machado
    Journal of Computer Science and Technology, 2013, 28 : 932 - 947