Wang, J., Wu, W., Liao, Z., Sangaiah, A. K. and Sherratt, R. S.
ORCID: https://orcid.org/0000-0001-7899-4445
(2019)
An energy-efficient off-loading scheme for low latency in collaborative edge computing.
IEEE Access, 7.
pp. 149182-149190.
ISSN 2169-3536
doi: 10.1109/ACCESS.2019.2946683
Abstract/Summary
Mobile terminal users applications, such as smartphones or laptops, have frequent computational task demanding but limited battery power. Edge computing is introduced to offload terminals' tasks to meet the quality of service requirements such as low delay and energy consumption. By offloading computation tasks, edge servers can enable terminals to collaboratively run the highly demanding applications in acceptable delay requirements. However, existing schemes barely consider the characteristics of the edge server, which leads to random assignment of tasks among servers and big tasks with high computational intensity (named as “big task”) may be assigned to servers with low ability. In this paper, a task is divided into several subtasks and subtasks are offloaded according to characteristics of edge servers, such as transmission distance and central processing unit (CPU) capacity. With this multi-subtasks-to-multi-servers model, an adaptive offloading scheme based on Hungarian algorithm is proposed with low complexity. Extensive simulations are conducted to show the efficiency of the scheme on reducing the offloading latency with low energy consumption.
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| Item Type | Article |
| URI | https://reading-clone.eprints-hosting.org/id/eprint/86911 |
| Identification Number/DOI | 10.1109/ACCESS.2019.2946683 |
| Refereed | Yes |
| Divisions | Life Sciences > School of Biological Sciences > Biomedical Sciences Life Sciences > School of Biological Sciences > Department of Bio-Engineering |
| Publisher | IEEE |
| Download/View statistics | View download statistics for this item |
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