HVC: A Hybrid Cloud Computing Framework in Vehicular Environments

Jingyun Feng, Zhi Liu, Celimuge Wu, Yusheng Ji

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

As increasingly more applications are deployed in vehicles, how to provide the demanded computational capability becomes crucial. This paper proposes the hybrid vehicular cloud (HVC) framework for cloud computing on the road to increase the computational capability of vehicles by using resources from the centralized cloud, RSU, and neighboring vehicles. The proposed scheme can be used as a general framework for all types of applications. It is able to satisfy various types of job requirements, such as real time or host requirements, and it is adaptive to the dynamic vehicular environment. Specifically, this paper defines the procedures to support the autonomous organization of a vehicular cloud. An online scheduling algorithm is proposed to solve the job assignment problem with the objective of processing more jobs and reducing cellular network usage. Extensive simulations are conducted, and the results show the superiority of the proposed scheme over competing schemes in typical urban scenarios.

Original languageEnglish
Title of host publicationProceedings - 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages9-16
Number of pages8
ISBN (Electronic)9781509063253
DOIs
Publication statusPublished - 2017 Jun 8
Event5th IEEE International Conference on Mobile Cloud Computing, Services and Engineering, MobileCloud 2017 - San Francisco, United States
Duration: 2017 Apr 72017 Apr 9

Other

Other5th IEEE International Conference on Mobile Cloud Computing, Services and Engineering, MobileCloud 2017
CountryUnited States
CitySan Francisco
Period17/4/717/4/9

Fingerprint

Cloud computing
Scheduling algorithms
Processing

Keywords

  • Cloud computing
  • Job scheduling
  • Vehicular cloud computing
  • Vehicular network

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture

Cite this

Feng, J., Liu, Z., Wu, C., & Ji, Y. (2017). HVC: A Hybrid Cloud Computing Framework in Vehicular Environments. In Proceedings - 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2017 (pp. 9-16). [7944866] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MobileCloud.2017.9

HVC : A Hybrid Cloud Computing Framework in Vehicular Environments. / Feng, Jingyun; Liu, Zhi; Wu, Celimuge; Ji, Yusheng.

Proceedings - 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 9-16 7944866.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Feng, J, Liu, Z, Wu, C & Ji, Y 2017, HVC: A Hybrid Cloud Computing Framework in Vehicular Environments. in Proceedings - 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2017., 7944866, Institute of Electrical and Electronics Engineers Inc., pp. 9-16, 5th IEEE International Conference on Mobile Cloud Computing, Services and Engineering, MobileCloud 2017, San Francisco, United States, 17/4/7. https://doi.org/10.1109/MobileCloud.2017.9
Feng J, Liu Z, Wu C, Ji Y. HVC: A Hybrid Cloud Computing Framework in Vehicular Environments. In Proceedings - 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 9-16. 7944866 https://doi.org/10.1109/MobileCloud.2017.9
Feng, Jingyun ; Liu, Zhi ; Wu, Celimuge ; Ji, Yusheng. / HVC : A Hybrid Cloud Computing Framework in Vehicular Environments. Proceedings - 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 9-16
@inproceedings{e46ff12a45b844bab9e1651c762a5f11,
title = "HVC: A Hybrid Cloud Computing Framework in Vehicular Environments",
abstract = "As increasingly more applications are deployed in vehicles, how to provide the demanded computational capability becomes crucial. This paper proposes the hybrid vehicular cloud (HVC) framework for cloud computing on the road to increase the computational capability of vehicles by using resources from the centralized cloud, RSU, and neighboring vehicles. The proposed scheme can be used as a general framework for all types of applications. It is able to satisfy various types of job requirements, such as real time or host requirements, and it is adaptive to the dynamic vehicular environment. Specifically, this paper defines the procedures to support the autonomous organization of a vehicular cloud. An online scheduling algorithm is proposed to solve the job assignment problem with the objective of processing more jobs and reducing cellular network usage. Extensive simulations are conducted, and the results show the superiority of the proposed scheme over competing schemes in typical urban scenarios.",
keywords = "Cloud computing, Job scheduling, Vehicular cloud computing, Vehicular network",
author = "Jingyun Feng and Zhi Liu and Celimuge Wu and Yusheng Ji",
year = "2017",
month = "6",
day = "8",
doi = "10.1109/MobileCloud.2017.9",
language = "English",
pages = "9--16",
booktitle = "Proceedings - 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

TY - GEN

T1 - HVC

T2 - A Hybrid Cloud Computing Framework in Vehicular Environments

AU - Feng, Jingyun

AU - Liu, Zhi

AU - Wu, Celimuge

AU - Ji, Yusheng

PY - 2017/6/8

Y1 - 2017/6/8

N2 - As increasingly more applications are deployed in vehicles, how to provide the demanded computational capability becomes crucial. This paper proposes the hybrid vehicular cloud (HVC) framework for cloud computing on the road to increase the computational capability of vehicles by using resources from the centralized cloud, RSU, and neighboring vehicles. The proposed scheme can be used as a general framework for all types of applications. It is able to satisfy various types of job requirements, such as real time or host requirements, and it is adaptive to the dynamic vehicular environment. Specifically, this paper defines the procedures to support the autonomous organization of a vehicular cloud. An online scheduling algorithm is proposed to solve the job assignment problem with the objective of processing more jobs and reducing cellular network usage. Extensive simulations are conducted, and the results show the superiority of the proposed scheme over competing schemes in typical urban scenarios.

AB - As increasingly more applications are deployed in vehicles, how to provide the demanded computational capability becomes crucial. This paper proposes the hybrid vehicular cloud (HVC) framework for cloud computing on the road to increase the computational capability of vehicles by using resources from the centralized cloud, RSU, and neighboring vehicles. The proposed scheme can be used as a general framework for all types of applications. It is able to satisfy various types of job requirements, such as real time or host requirements, and it is adaptive to the dynamic vehicular environment. Specifically, this paper defines the procedures to support the autonomous organization of a vehicular cloud. An online scheduling algorithm is proposed to solve the job assignment problem with the objective of processing more jobs and reducing cellular network usage. Extensive simulations are conducted, and the results show the superiority of the proposed scheme over competing schemes in typical urban scenarios.

KW - Cloud computing

KW - Job scheduling

KW - Vehicular cloud computing

KW - Vehicular network

UR - http://www.scopus.com/inward/record.url?scp=85021869883&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85021869883&partnerID=8YFLogxK

U2 - 10.1109/MobileCloud.2017.9

DO - 10.1109/MobileCloud.2017.9

M3 - Conference contribution

AN - SCOPUS:85021869883

SP - 9

EP - 16

BT - Proceedings - 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2017

PB - Institute of Electrical and Electronics Engineers Inc.

ER -