V-WorkGen: Virtual Workload Generation Tool for Connected Automotive Services

Yin Chen Liu; Baek Gyu Kim

doi:10.1109/BigData50022.2020.9378320

V-WorkGen: Virtual Workload Generation Tool for Connected Automotive Services

Yin Chen Liu
, Baek Gyu Kim

Department of Electrical Engineering and Computer Science

InfoTech Labs

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

Abstract

Connected car is one of the major trends in the auto-motive industry to provide users with advanced services to improve driving quality and safety. For example, a predictive maintenance service identifies any malfunction of vehicles by analyzing sensor data sent from them; High-Definition (HD) map can be constructed by collecting sensor data from multiple vehicles, and distributed to them to enhance the quality of any autonomous features.

Original language	English
Title of host publication	Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020
Editors	Xintao Wu, Chris Jermaine, Li Xiong, Xiaohua Tony Hu, Olivera Kotevska, Siyuan Lu, Weijia Xu, Srinivas Aluru, Chengxiang Zhai, Eyhab Al-Masri, Zhiyuan Chen, Jeff Saltz
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1780-1783
Number of pages	4
ISBN (Electronic)	9781728162515
DOIs	https://doi.org/10.1109/BigData50022.2020.9378320
State	Published - 10 Dec 2020
Event	8th IEEE International Conference on Big Data, Big Data 2020 - Virtual, Online, United States Duration: 10 Dec 2020 → 13 Dec 2020

Publication series

Name	Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020

Conference

Conference	8th IEEE International Conference on Big Data, Big Data 2020
Country/Territory	United States
City	Virtual, Online
Period	10/12/20 → 13/12/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Access to Document

10.1109/BigData50022.2020.9378320

Cite this

Liu, Y. C., & Kim, B. G. (2020). V-WorkGen: Virtual Workload Generation Tool for Connected Automotive Services. In X. Wu, C. Jermaine, L. Xiong, X. T. Hu, O. Kotevska, S. Lu, W. Xu, S. Aluru, C. Zhai, E. Al-Masri, Z. Chen, & J. Saltz (Eds.), Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020 (pp. 1780-1783). Article 9378320 (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData50022.2020.9378320

Liu, Yin Chen ; Kim, Baek Gyu. / V-WorkGen : Virtual Workload Generation Tool for Connected Automotive Services. Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. editor / Xintao Wu ; Chris Jermaine ; Li Xiong ; Xiaohua Tony Hu ; Olivera Kotevska ; Siyuan Lu ; Weijia Xu ; Srinivas Aluru ; Chengxiang Zhai ; Eyhab Al-Masri ; Zhiyuan Chen ; Jeff Saltz. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 1780-1783 (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020).

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title = "V-WorkGen: Virtual Workload Generation Tool for Connected Automotive Services",

abstract = "Connected car is one of the major trends in the auto-motive industry to provide users with advanced services to improve driving quality and safety. For example, a predictive maintenance service identifies any malfunction of vehicles by analyzing sensor data sent from them; High-Definition (HD) map can be constructed by collecting sensor data from multiple vehicles, and distributed to them to enhance the quality of any autonomous features.",

author = "Liu, \{Yin Chen\} and Kim, \{Baek Gyu\}",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 8th IEEE International Conference on Big Data, Big Data 2020 ; Conference date: 10-12-2020 Through 13-12-2020",

year = "2020",

month = dec,

day = "10",

doi = "10.1109/BigData50022.2020.9378320",

language = "English",

series = "Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1780--1783",

editor = "Xintao Wu and Chris Jermaine and Li Xiong and Hu, \{Xiaohua Tony\} and Olivera Kotevska and Siyuan Lu and Weijia Xu and Srinivas Aluru and Chengxiang Zhai and Eyhab Al-Masri and Zhiyuan Chen and Jeff Saltz",

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Liu, YC & Kim, BG 2020, V-WorkGen: Virtual Workload Generation Tool for Connected Automotive Services. in X Wu, C Jermaine, L Xiong, XT Hu, O Kotevska, S Lu, W Xu, S Aluru, C Zhai, E Al-Masri, Z Chen & J Saltz (eds), Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020., 9378320, Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020, Institute of Electrical and Electronics Engineers Inc., pp. 1780-1783, 8th IEEE International Conference on Big Data, Big Data 2020, Virtual, Online, United States, 10/12/20. https://doi.org/10.1109/BigData50022.2020.9378320

V-WorkGen: Virtual Workload Generation Tool for Connected Automotive Services. / Liu, Yin Chen; Kim, Baek Gyu.
Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. ed. / Xintao Wu; Chris Jermaine; Li Xiong; Xiaohua Tony Hu; Olivera Kotevska; Siyuan Lu; Weijia Xu; Srinivas Aluru; Chengxiang Zhai; Eyhab Al-Masri; Zhiyuan Chen; Jeff Saltz. Institute of Electrical and Electronics Engineers Inc., 2020. p. 1780-1783 9378320 (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020).

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

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T1 - V-WorkGen

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AU - Liu, Yin Chen

AU - Kim, Baek Gyu

PY - 2020/12/10

Y1 - 2020/12/10

N2 - Connected car is one of the major trends in the auto-motive industry to provide users with advanced services to improve driving quality and safety. For example, a predictive maintenance service identifies any malfunction of vehicles by analyzing sensor data sent from them; High-Definition (HD) map can be constructed by collecting sensor data from multiple vehicles, and distributed to them to enhance the quality of any autonomous features.

AB - Connected car is one of the major trends in the auto-motive industry to provide users with advanced services to improve driving quality and safety. For example, a predictive maintenance service identifies any malfunction of vehicles by analyzing sensor data sent from them; High-Definition (HD) map can be constructed by collecting sensor data from multiple vehicles, and distributed to them to enhance the quality of any autonomous features.

UR - https://www.scopus.com/pages/publications/85103850691

U2 - 10.1109/BigData50022.2020.9378320

DO - 10.1109/BigData50022.2020.9378320

M3 - Conference contribution

AN - SCOPUS:85103850691

T3 - Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020

SP - 1780

EP - 1783

BT - Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020

A2 - Wu, Xintao

A2 - Jermaine, Chris

A2 - Xiong, Li

A2 - Hu, Xiaohua Tony

A2 - Kotevska, Olivera

A2 - Lu, Siyuan

A2 - Xu, Weijia

A2 - Aluru, Srinivas

A2 - Zhai, Chengxiang

A2 - Al-Masri, Eyhab

A2 - Chen, Zhiyuan

A2 - Saltz, Jeff

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 10 December 2020 through 13 December 2020

ER -

Liu YC, Kim BG. V-WorkGen: Virtual Workload Generation Tool for Connected Automotive Services. In Wu X, Jermaine C, Xiong L, Hu XT, Kotevska O, Lu S, Xu W, Aluru S, Zhai C, Al-Masri E, Chen Z, Saltz J, editors, Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 1780-1783. 9378320. (Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020). doi: 10.1109/BigData50022.2020.9378320

V-WorkGen: Virtual Workload Generation Tool for Connected Automotive Services

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