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    Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Systems Architecture. 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 Journal of Systems Architecture, 114, 2021 DOI: 10.1016/j.sysarc.2020.101970

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Task scheduling with precedence and placement constraints for resource utilization improvement in multi-user MEC environment

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Task scheduling with precedence and placement constraints for resource utilization improvement in multi-user MEC environment. / Liu, B.; Xu, X.; Qi, L. et al.
In: Journal of Systems Architecture, Vol. 114, 101970, 01.03.2021.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Liu B, Xu X, Qi L, Ni Q, Dou W. Task scheduling with precedence and placement constraints for resource utilization improvement in multi-user MEC environment. Journal of Systems Architecture. 2021 Mar 1;114:101970. Epub 2020 Dec 11. doi: 10.1016/j.sysarc.2020.101970

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Liu, B. ; Xu, X. ; Qi, L. et al. / Task scheduling with precedence and placement constraints for resource utilization improvement in multi-user MEC environment. In: Journal of Systems Architecture. 2021 ; Vol. 114.

Bibtex

@article{cd6a5602a9bf4e5a99ce4af033554bae,
title = "Task scheduling with precedence and placement constraints for resource utilization improvement in multi-user MEC environment",
abstract = "Efficient task scheduling improves offloading performance in mobile edge computing (MEC) environment. The jobs offloaded by different users would have different dependent tasks with diverse resource demands at different times. Meanwhile, due to the heterogeneity of edge servers configurations in MEC, offloaded jobs may frequently have placement constraints, restricting them to run on a particular class of edge servers meeting specific software running settings. This spatio-temporal information gives the opportunity to improve the resource utilization of the computing system. In this paper, we study the scheduling method for the jobs consisting of dependent tasks offloaded by different users in MEC. A new task offloading scheduler, Horae, is proposed to not only improve the resource utilization of MEC environment but also guarantees to select the edge server which could satisfy placement constraints for each offloaded task. Concretely, considering the fact that each job would experience slack time as a result of competing for limited resource with other jobs in MEC, Horae minimizes the sum of all slack time values of all the jobs while guaranteeing placement constraints, and therefore improve the resource utilization of the system. Horae was validated for its feasibility and efficiency by means of extensive experiments, which are presented in this paper. ",
keywords = "Mobile edge computing, Offloading, Precedence constraints, Resource utilization, Multitasking, Computing system, Dependent tasks, Resource demands, Resource utilizations, Scheduling methods, Spatiotemporal information, Task offloading, Task-scheduling, Scheduling",
author = "B. Liu and X. Xu and L. Qi and Q. Ni and W. Dou",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Journal of Systems Architecture. 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 Journal of Systems Architecture, 114, 2021 DOI: 10.1016/j.sysarc.2020.101970",
year = "2021",
month = mar,
day = "1",
doi = "10.1016/j.sysarc.2020.101970",
language = "English",
volume = "114",
journal = "Journal of Systems Architecture",
issn = "1383-7621",
publisher = "Elsevier Science B.V.",

}

RIS

TY - JOUR

T1 - Task scheduling with precedence and placement constraints for resource utilization improvement in multi-user MEC environment

AU - Liu, B.

AU - Xu, X.

AU - Qi, L.

AU - Ni, Q.

AU - Dou, W.

N1 - This is the author’s version of a work that was accepted for publication in Journal of Systems Architecture. 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 Journal of Systems Architecture, 114, 2021 DOI: 10.1016/j.sysarc.2020.101970

PY - 2021/3/1

Y1 - 2021/3/1

N2 - Efficient task scheduling improves offloading performance in mobile edge computing (MEC) environment. The jobs offloaded by different users would have different dependent tasks with diverse resource demands at different times. Meanwhile, due to the heterogeneity of edge servers configurations in MEC, offloaded jobs may frequently have placement constraints, restricting them to run on a particular class of edge servers meeting specific software running settings. This spatio-temporal information gives the opportunity to improve the resource utilization of the computing system. In this paper, we study the scheduling method for the jobs consisting of dependent tasks offloaded by different users in MEC. A new task offloading scheduler, Horae, is proposed to not only improve the resource utilization of MEC environment but also guarantees to select the edge server which could satisfy placement constraints for each offloaded task. Concretely, considering the fact that each job would experience slack time as a result of competing for limited resource with other jobs in MEC, Horae minimizes the sum of all slack time values of all the jobs while guaranteeing placement constraints, and therefore improve the resource utilization of the system. Horae was validated for its feasibility and efficiency by means of extensive experiments, which are presented in this paper.

AB - Efficient task scheduling improves offloading performance in mobile edge computing (MEC) environment. The jobs offloaded by different users would have different dependent tasks with diverse resource demands at different times. Meanwhile, due to the heterogeneity of edge servers configurations in MEC, offloaded jobs may frequently have placement constraints, restricting them to run on a particular class of edge servers meeting specific software running settings. This spatio-temporal information gives the opportunity to improve the resource utilization of the computing system. In this paper, we study the scheduling method for the jobs consisting of dependent tasks offloaded by different users in MEC. A new task offloading scheduler, Horae, is proposed to not only improve the resource utilization of MEC environment but also guarantees to select the edge server which could satisfy placement constraints for each offloaded task. Concretely, considering the fact that each job would experience slack time as a result of competing for limited resource with other jobs in MEC, Horae minimizes the sum of all slack time values of all the jobs while guaranteeing placement constraints, and therefore improve the resource utilization of the system. Horae was validated for its feasibility and efficiency by means of extensive experiments, which are presented in this paper.

KW - Mobile edge computing

KW - Offloading

KW - Precedence constraints

KW - Resource utilization

KW - Multitasking

KW - Computing system

KW - Dependent tasks

KW - Resource demands

KW - Resource utilizations

KW - Scheduling methods

KW - Spatiotemporal information

KW - Task offloading

KW - Task-scheduling

KW - Scheduling

U2 - 10.1016/j.sysarc.2020.101970

DO - 10.1016/j.sysarc.2020.101970

M3 - Journal article

VL - 114

JO - Journal of Systems Architecture

JF - Journal of Systems Architecture

SN - 1383-7621

M1 - 101970

ER -