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
Accepted author manuscript, 1.26 MB, PDF document
Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
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 -