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    Rights statement: This is the author’s version of a work that was accepted for publication in Future Generation Computer Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Future Generation Computer Systems, 85, 2018 DOI: 10.1016/j.future.2018.02.014

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User mobility aware task assignment for mobile edge computing

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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User mobility aware task assignment for mobile edge computing. / Wang, Zi; Zhao, Zhiwei; Min, Geyong et al.
In: Future Generation Computer Systems, Vol. 85, 08.2018, p. 1-8.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Wang, Z, Zhao, Z, Min, G, Huang, X, Ni, Q & Wang, R 2018, 'User mobility aware task assignment for mobile edge computing', Future Generation Computer Systems, vol. 85, pp. 1-8. https://doi.org/10.1016/j.future.2018.02.014

APA

Wang, Z., Zhao, Z., Min, G., Huang, X., Ni, Q., & Wang, R. (2018). User mobility aware task assignment for mobile edge computing. Future Generation Computer Systems, 85, 1-8. https://doi.org/10.1016/j.future.2018.02.014

Vancouver

Wang Z, Zhao Z, Min G, Huang X, Ni Q, Wang R. User mobility aware task assignment for mobile edge computing. Future Generation Computer Systems. 2018 Aug;85:1-8. Epub 2018 Mar 16. doi: 10.1016/j.future.2018.02.014

Author

Wang, Zi ; Zhao, Zhiwei ; Min, Geyong et al. / User mobility aware task assignment for mobile edge computing. In: Future Generation Computer Systems. 2018 ; Vol. 85. pp. 1-8.

Bibtex

@article{6856f6dc59834863b8ecb2aa4ae7b683,
title = "User mobility aware task assignment for mobile edge computing",
abstract = "Mobile Edge Computing (MEC) has emerged as a prospective computing paradigm to provide pervasive computing and storage services for mobile and big data applications. In MEC, many small cell base stations (sBSs) are deployed to establish a mobile edge network (MEN). These sBSs can be usually accessed directly by mobile users. The computational tasks are first offloaded from mobile users to the MEN and then executed in one or several specific sBSs in the MEN. While the offloading decision has been well studied, the task execution delay on the MEN side is overlooked. This paper aims at reducing the task execution delay by task scheduling in MENs. Specifically, we jointly consider the task properties, the user mobility and network constraints. The problem is formalized as a constraint satisfaction problem and a lightweight heuristic solution is proposed for fast scheduling. We conduct simulation experiments to study the performance of the proposed work. The results show that our work is able to significantly reduce the task execution delay in MENs and thus reduces the end-to-end delay for MEC tasks.",
keywords = "Mobile edge computing, Task assignment, User mobility, Offloading",
author = "Zi Wang and Zhiwei Zhao and Geyong Min and Xinyuan Huang and Qiang Ni and Rong Wang",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Future Generation Computer Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Future Generation Computer Systems, 85, 2018 DOI: 10.1016/j.future.2018.02.014",
year = "2018",
month = aug,
doi = "10.1016/j.future.2018.02.014",
language = "English",
volume = "85",
pages = "1--8",
journal = "Future Generation Computer Systems",
issn = "0167-739X",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - User mobility aware task assignment for mobile edge computing

AU - Wang, Zi

AU - Zhao, Zhiwei

AU - Min, Geyong

AU - Huang, Xinyuan

AU - Ni, Qiang

AU - Wang, Rong

N1 - This is the author’s version of a work that was accepted for publication in Future Generation Computer Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Future Generation Computer Systems, 85, 2018 DOI: 10.1016/j.future.2018.02.014

PY - 2018/8

Y1 - 2018/8

N2 - Mobile Edge Computing (MEC) has emerged as a prospective computing paradigm to provide pervasive computing and storage services for mobile and big data applications. In MEC, many small cell base stations (sBSs) are deployed to establish a mobile edge network (MEN). These sBSs can be usually accessed directly by mobile users. The computational tasks are first offloaded from mobile users to the MEN and then executed in one or several specific sBSs in the MEN. While the offloading decision has been well studied, the task execution delay on the MEN side is overlooked. This paper aims at reducing the task execution delay by task scheduling in MENs. Specifically, we jointly consider the task properties, the user mobility and network constraints. The problem is formalized as a constraint satisfaction problem and a lightweight heuristic solution is proposed for fast scheduling. We conduct simulation experiments to study the performance of the proposed work. The results show that our work is able to significantly reduce the task execution delay in MENs and thus reduces the end-to-end delay for MEC tasks.

AB - Mobile Edge Computing (MEC) has emerged as a prospective computing paradigm to provide pervasive computing and storage services for mobile and big data applications. In MEC, many small cell base stations (sBSs) are deployed to establish a mobile edge network (MEN). These sBSs can be usually accessed directly by mobile users. The computational tasks are first offloaded from mobile users to the MEN and then executed in one or several specific sBSs in the MEN. While the offloading decision has been well studied, the task execution delay on the MEN side is overlooked. This paper aims at reducing the task execution delay by task scheduling in MENs. Specifically, we jointly consider the task properties, the user mobility and network constraints. The problem is formalized as a constraint satisfaction problem and a lightweight heuristic solution is proposed for fast scheduling. We conduct simulation experiments to study the performance of the proposed work. The results show that our work is able to significantly reduce the task execution delay in MENs and thus reduces the end-to-end delay for MEC tasks.

KW - Mobile edge computing

KW - Task assignment

KW - User mobility

KW - Offloading

U2 - 10.1016/j.future.2018.02.014

DO - 10.1016/j.future.2018.02.014

M3 - Journal article

VL - 85

SP - 1

EP - 8

JO - Future Generation Computer Systems

JF - Future Generation Computer Systems

SN - 0167-739X

ER -