Research Article
Edge Computing-Based Multitasking Strategies in Smart Grids
@INPROCEEDINGS{10.1007/978-3-031-32443-7_14, author={Han Zhao and Mengxuan Dai and Kaiwen Ji and Wenshan Wei and Xinghong Jiang and Yong Ma and Yunni Xia and Bingbing He}, title={Edge Computing-Based Multitasking Strategies in Smart Grids}, proceedings={Mobile Networks and Management. 12th EAI International Conference, MONAMI 2022, Virtual Event, October 29-31, 2022, Proceedings}, proceedings_a={MONAMI}, year={2023}, month={5}, keywords={edge computing Smart grid task assignment particle swarm algorithm multi-objective constraints}, doi={10.1007/978-3-031-32443-7_14} }- Han Zhao
Mengxuan Dai
Kaiwen Ji
Wenshan Wei
Xinghong Jiang
Yong Ma
Yunni Xia
Bingbing He
Year: 2023
Edge Computing-Based Multitasking Strategies in Smart Grids
MONAMI
Springer
DOI: 10.1007/978-3-031-32443-7_14
Abstract
In order to promote the digital development of the smart grid, power data needs to be analyzed and processed in real time, but because the number of power grid terminal devices is vast, the massive amount of data generated will incur additional network latency and communication costs if processed directly by cloud servers, and there is also a risk of data leakage. Therefore, power data is considered to be placed on edge servers for processing to overcome many problems in the current cloud computing paradigm for power systems, such as the inability to fully realize the requirements of high bandwidth and low latency. This paper thus proposes a multitask assignment strategy (MPA) for smart grid terminals based on edge computing. The method first classifies grid end tasks into different classes based on the size of data, security level, and computational workload; it then selects a suitable edge server for the smart grid terminal tasks using the particle swarm algorithm. The simulation results show the effectiveness of the method in this paper.
