Research Article
Software-Defined Task Scheduling Strategy Towards Edge Computing
@INPROCEEDINGS{10.1007/978-3-030-89814-4_15, author={Yue Guo and Junfeng Hou and Heng Wang and Changjin Li and Hongjun Zhang and Guangxu Zhou and Xudong Zhao}, title={Software-Defined Task Scheduling Strategy Towards Edge Computing}, proceedings={Mobile Multimedia Communications. 14th EAI International Conference, Mobimedia 2021, Virtual Event, July 23-25, 2021, Proceedings}, proceedings_a={MOBIMEDIA}, year={2021}, month={11}, keywords={Edge computing Task scheduling Software-defined}, doi={10.1007/978-3-030-89814-4_15} }- Yue Guo
Junfeng Hou
Heng Wang
Changjin Li
Hongjun Zhang
Guangxu Zhou
Xudong Zhao
Year: 2021
Software-Defined Task Scheduling Strategy Towards Edge Computing
MOBIMEDIA
Springer
DOI: 10.1007/978-3-030-89814-4_15
Abstract
Data processing has posed new challenges to transmission bandwidth and computing load under the existing cloud computing architectures. In this paper, a software-defined task cooperative scheduling structure is proposed towards edge computing. Specifically, a clustering algorithm based on two-way selection between idle users and overloaded users is firstly designed, which combines the historical information of idle users and the interest similarity of overloaded users to form the stable cooperative clusters. Then, a sub-task partitioning algorithm based on the optimal delay is presented to achieve the overall optimal delay with the guarantee that sub-tasks are completed simultaneously. Numerical results show that the proposed strategy is not only able to save the data transmission bandwidth significantly, but also achieve the optimal delay while ensuring the stability of cooperative clusters.
