Abstract
In this paper, priority-based mobile edge computing technology is used to decide the task migration problem on telemedicine devices. Tasks can be adaptively assigned to mobile edge servers or processed locally according to the current network situation and specific task processing environment, thus improving the efficiency and quality of telemedicine services. The main work of this paper is in three aspects. Firstly, priority is set for urgent tasks, and non-preemptive priority queues are set on the server side of MEC, so that the average stay time of each priority can be calculated according to the current situation of priority tasks queuing. Secondly, in the process of task transmission to the server, the channel resources are allocated adaptively by priority-based twice filtering strategy, and the final task migration decision is obtained by auction algorithm. Thirdly, compared with the existing mobile edge computing task migration model, the priority-based task migration model greatly guarantees the real-time and high quality of telemedicine.
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Acknowledgements
This work is jointly supported by the National Natural Science Foundation of China (No. 61601082, No. 61471100, No. 61701503, No. 61750110527).
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Zhu, Y., Tang, Y., Wu, C., Lin, D. (2020). Research on Multi-priority Task Scheduling Algorithms for Mobile Edge Computing. In: Liang, Q., Wang, W., Mu, J., Liu, X., Na, Z., Chen, B. (eds) Artificial Intelligence in China. Lecture Notes in Electrical Engineering, vol 572. Springer, Singapore. https://doi.org/10.1007/978-981-15-0187-6_16
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DOI: https://doi.org/10.1007/978-981-15-0187-6_16
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