5G SA network slicing security mapping algorithm based on Bayes evaluation
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1.School of Computer Science, Nanjing University of Posts and Telecommunications;2.Suzhou Industrial Park Institute of Services Outsourcing;3.School of Computer Science &4.Technology, Soochow University;5.Ruijie Networks Co., Ltd.

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TP393

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    Abstract:

    The development of 5G network promotes the strategic transformation and upgrading of the vertical industry of the industrial Internet. The 5G SA (Stand-Alone) network sinks the user plane function (UPF) into the business area, and the control plane remains in the center of the large area. All business data is accessed through the 5G edge computing interface (MEC) to the business application server, and all traffic for users to access their own servers is completed internally, which meets network security requirements and minimizes business path delay. Through optimized particle swarm optimization (PSO), a fitness function based on network physical node resources and link resources is constructed, and the Bayesian evaluation method is introduced to calculate the physical node isolation factor. A threshold is set as the average isolation factor of all nodes as a constraint condition to ensure the isolation performance of network slices, and iterative solution is used to adjust the path resources between network slices to improve network performance. After the actual 5G network test of the Intelligence mine, the results show that the algorithm can increase the revenue-cost ratio by 10%, increase the link utilization rate by 19%, and increase the uplink rate by 20%-50%, which fully guarantees the service quality of the mining area network.

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History
  • Received:December 28,2021
  • Revised:March 10,2022
  • Adopted:March 11,2022
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