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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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 - 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 -