期刊
JOURNAL OF SYSTEMS ARCHITECTURE
卷 114, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.sysarc.2020.101970
关键词
Mobile edge computing; Offloading; Precedence constraints; Resource utilization
资金
- National Natural Science Foundation of China [61672276]
- Key Research and Development Project of Jiangsu Province, China [BE2019104]
- National Science Foundation of China [61872219]
- Natural Science Foundation of Shandong Province [ZR2019MF001]
- Open Project of State Key Laboratory for Novel Software Technology [KFKT2020B08]
- Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing University, China
Efficient task scheduling plays a crucial role in enhancing offloading performance in the MEC environment. The proposed Horae scheduler aims to improve resource utilization and ensure placement constraints for offloaded tasks. Extensive experiments have validated the feasibility and efficiency of Horae in improving system resource utilization.
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.
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