Abstract
Nowadays, Mobile Edge Computing (MEC) has become an effective solution to the problem of insufficient computing power of mobile terminals. However, edge computing also has some limitations, the variability of the edge environment makes resource scheduling in edge computing difficult. Especially in the face of large-flow data processing caused by emergencies, there is still a lack of in-depth research and exploration. In order to solve this problem, this paper proposes an resource scheduling algorithms for burst network flow in edge computing. When the MEC server encounters an burst event, the algorithm uses a certain number of edge servers near the incident site as a cluster to uniformly perform resource scheduling and task allocation to alleviate the pressure on the MEC server that encountered the burst event, thereby efficiently processing service requests in this scenarios. This paper uses python to build a simulation platform and implement algorithms. And we designed a simulation experiment to compare the average response time of service requests, server load and other indicators with Markov approximation algorithm, exhaustive search algorithm and other benchmark algorithms. Simulation analysis shows that the algorithm we proposed performs better than these algorithms when encounters an burst event.
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Acknowledgement
This work is supported by National Key R&D Program of China (2020YFB1807802).
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Yan, J., Rui, L., Yang, Y., Chen, S., Chen, X. (2022). Resource Scheduling Algorithms for Burst Network Flow in Edge Computing. In: Liu, Q., Liu, X., Chen, B., Zhang, Y., Peng, J. (eds) Proceedings of the 11th International Conference on Computer Engineering and Networks. Lecture Notes in Electrical Engineering, vol 808. Springer, Singapore. https://doi.org/10.1007/978-981-16-6554-7_173
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DOI: https://doi.org/10.1007/978-981-16-6554-7_173
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