A demonstration of B-EagleV Visualizing massive point cloud directly from HDFS

Minh Hieu Nguyen; Sanghyun Yoon; Sangyoon Park; Joon Heo

doi:10.1109/BigData47090.2019.9005717

A demonstration of B-EagleV Visualizing massive point cloud directly from HDFS

Minh Hieu Nguyen, Sanghyun Yoon, Sangyoon Park, Joon Heo

Department of Civil and Environmental Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

The advent of Hadoop has inspired many researchers to conduct studies on big data. These studies have covered a wide range of aspects of big spatial data. However, they still face challenges in visualizing big spatial data on a distributed storage model since loading multi-resolution data is inefficient. For this reason, multi-resolution data are usually excluded from the distributed storage model to speed up the loading process. This limitation prompted the introduction of B-EagleV, a novel Hadoop-based solution that enables users to manage and visualize massive point cloud data on Hadoop Distributed File System (HDFS) without moving the multi-resolution data to a local server. This paper presents the achievements of B-EagleV in efforts to discover the values of Hadoop in visualizing massive point cloud data.

Original language	English
Title of host publication	Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
Editors	Chaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4121-4124
Number of pages	4
ISBN (Electronic)	9781728108582
DOIs	https://doi.org/10.1109/BigData47090.2019.9005717
Publication status	Published - 2019 Dec
Event	2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States Duration: 2019 Dec 9 → 2019 Dec 12

Publication series

Name	Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

Conference

Conference	2019 IEEE International Conference on Big Data, Big Data 2019
Country/Territory	United States
City	Los Angeles
Period	19/12/9 → 19/12/12

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science and ICT) (No. 2018R1A2B2009160).

Publisher Copyright:
© 2019 IEEE.

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Networks and Communications
Information Systems
Information Systems and Management

Access to Document

10.1109/BigData47090.2019.9005717

Cite this

Nguyen, M. H., Yoon, S., Park, S., & Heo, J. (2019). A demonstration of B-EagleV Visualizing massive point cloud directly from HDFS. In C. Baru, J. Huan, L. Khan, X. T. Hu, R. Ak, Y. Tian, R. Barga, C. Zaniolo, K. Lee, & Y. F. Ye (Eds.), Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 (pp. 4121-4124). [9005717] (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData47090.2019.9005717

Nguyen, Minh Hieu ; Yoon, Sanghyun ; Park, Sangyoon et al. / A demonstration of B-EagleV Visualizing massive point cloud directly from HDFS. Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. editor / Chaitanya Baru ; Jun Huan ; Latifur Khan ; Xiaohua Tony Hu ; Ronay Ak ; Yuanyuan Tian ; Roger Barga ; Carlo Zaniolo ; Kisung Lee ; Yanfang Fanny Ye. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 4121-4124 (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019).

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abstract = "The advent of Hadoop has inspired many researchers to conduct studies on big data. These studies have covered a wide range of aspects of big spatial data. However, they still face challenges in visualizing big spatial data on a distributed storage model since loading multi-resolution data is inefficient. For this reason, multi-resolution data are usually excluded from the distributed storage model to speed up the loading process. This limitation prompted the introduction of B-EagleV, a novel Hadoop-based solution that enables users to manage and visualize massive point cloud data on Hadoop Distributed File System (HDFS) without moving the multi-resolution data to a local server. This paper presents the achievements of B-EagleV in efforts to discover the values of Hadoop in visualizing massive point cloud data.",

author = "Nguyen, {Minh Hieu} and Sanghyun Yoon and Sangyoon Park and Joon Heo",

note = "Funding Information: ACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science and ICT) (No. 2018R1A2B2009160). Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Big Data, Big Data 2019 ; Conference date: 09-12-2019 Through 12-12-2019",

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doi = "10.1109/BigData47090.2019.9005717",

language = "English",

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Nguyen, MH, Yoon, S, Park, S & Heo, J 2019, A demonstration of B-EagleV Visualizing massive point cloud directly from HDFS. in C Baru, J Huan, L Khan, XT Hu, R Ak, Y Tian, R Barga, C Zaniolo, K Lee & YF Ye (eds), Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019., 9005717, Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019, Institute of Electrical and Electronics Engineers Inc., pp. 4121-4124, 2019 IEEE International Conference on Big Data, Big Data 2019, Los Angeles, United States, 19/12/9. https://doi.org/10.1109/BigData47090.2019.9005717

A demonstration of B-EagleV Visualizing massive point cloud directly from HDFS. / Nguyen, Minh Hieu; Yoon, Sanghyun; Park, Sangyoon et al.

Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. ed. / Chaitanya Baru; Jun Huan; Latifur Khan; Xiaohua Tony Hu; Ronay Ak; Yuanyuan Tian; Roger Barga; Carlo Zaniolo; Kisung Lee; Yanfang Fanny Ye. Institute of Electrical and Electronics Engineers Inc., 2019. p. 4121-4124 9005717 (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N1 - Funding Information: ACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science and ICT) (No. 2018R1A2B2009160). Publisher Copyright: © 2019 IEEE.

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A2 - Tian, Yuanyuan

A2 - Barga, Roger

A2 - Zaniolo, Carlo

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Nguyen MH, Yoon S, Park S, Heo J. A demonstration of B-EagleV Visualizing massive point cloud directly from HDFS. In Baru C, Huan J, Khan L, Hu XT, Ak R, Tian Y, Barga R, Zaniolo C, Lee K, Ye YF, editors, Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 4121-4124. 9005717. (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019). doi: 10.1109/BigData47090.2019.9005717

A demonstration of B-EagleV Visualizing massive point cloud directly from HDFS

Abstract

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Bibliographical note

All Science Journal Classification (ASJC) codes

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