(A)kNN query processing on the cloud: A survey

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Standard

(A)kNN query processing on the cloud: A survey. / Nodarakis, Nikolaos; Rapti, Angeliki; Sioutas, Spyros; Tsakalidis, Athanasios K.; Tsolis, Dimitrios; Tzimas, Giannis; Panagis, Yannis.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, 2017. p. 26-40 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 10230 LNCS).

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Harvard

Nodarakis, N, Rapti, A, Sioutas, S, Tsakalidis, AK, Tsolis, D, Tzimas, G & Panagis, Y 2017, (A)kNN query processing on the cloud: A survey. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10230 LNCS, pp. 26-40. https://doi.org/10.1007/978-3-319-57045-7_3

APA

Nodarakis, N., Rapti, A., Sioutas, S., Tsakalidis, A. K., Tsolis, D., Tzimas, G., & Panagis, Y. (2017). (A)kNN query processing on the cloud: A survey. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 26-40). Springer Verlag,. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10230 LNCS https://doi.org/10.1007/978-3-319-57045-7_3

Vancouver

Nodarakis N, Rapti A, Sioutas S, Tsakalidis AK, Tsolis D, Tzimas G et al. (A)kNN query processing on the cloud: A survey. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag,. 2017. p. 26-40. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 10230 LNCS). https://doi.org/10.1007/978-3-319-57045-7_3

Author

Nodarakis, Nikolaos ; Rapti, Angeliki ; Sioutas, Spyros ; Tsakalidis, Athanasios K. ; Tsolis, Dimitrios ; Tzimas, Giannis ; Panagis, Yannis. / (A)kNN query processing on the cloud: A survey. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, 2017. pp. 26-40 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 10230 LNCS).

Bibtex

@inbook{441936340a9e40928f72f6d0e71da570,
title = "(A)kNN query processing on the cloud: A survey",
abstract = "{\textcopyright} Springer International Publishing AG 2017. 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.",
keywords = "Big data, MapReduce, Nearest neighbour, NoSQL, Query processing",
author = "Nikolaos Nodarakis and Angeliki Rapti and Spyros Sioutas and Tsakalidis, {Athanasios K.} and Dimitrios Tsolis and Giannis Tzimas and Yannis Panagis",
year = "2017",
doi = "10.1007/978-3-319-57045-7_3",
language = "English",
isbn = "9783319570440",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag,",
pages = "26--40",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

RIS

TY - CHAP

T1 - (A)kNN query processing on the cloud: A survey

AU - Nodarakis, Nikolaos

AU - Rapti, Angeliki

AU - Sioutas, Spyros

AU - Tsakalidis, Athanasios K.

AU - Tsolis, Dimitrios

AU - Tzimas, Giannis

AU - Panagis, Yannis

PY - 2017

Y1 - 2017

N2 - © Springer International Publishing AG 2017. 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.

AB - © Springer International Publishing AG 2017. 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.

KW - Big data

KW - MapReduce

KW - Nearest neighbour

KW - NoSQL

KW - Query processing

UR - http://www.mendeley.com/research/aknn-query-processing-cloud-survey

U2 - 10.1007/978-3-319-57045-7_3

DO - 10.1007/978-3-319-57045-7_3

M3 - Book chapter

SN - 9783319570440

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 26

EP - 40

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

PB - Springer Verlag,

ER -

ID: 218484460