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We develop a scalable analytic model for capturing the 6G V2X service process, in which a latency-sensitive vehicle task can dynamically migrate between MEC servers as a result of vehicle flexibility. Solutions for computing efficiency metrics, including task rejection possibility and mean task response delay, are obtained. Mathematical analysis is used to show the effect of various specifications on the 6G V2X service efficiency.
Source link: https://doi.org/10.1007/s12083-021-01285-1
The survey states the crucial concerns of 5G network such as data protection and verification in addition to the countermeasures to get rid of these issues in 6G network. Lastly, the study wraps up with a new design suggestion based on the deep learning technique for implementation in a 6G network for verification by identifying the attack in network traffic.
Source link: https://doi.org/10.1007/978-981-16-4625-6_87
A smart building design in 5G with versatility for various deployment situations and service needs has enabled various service models for mobile network operators in both local and nationwide ranges. Future 6G networks will feature also more adaptable mobile network release driven by spectrum and infrastructure sharing among the drivers. The recommended framework offers an adaptability of network configuration for numerous operators in problem of open range and infrastructure market by utilizing a multi-dimensional matrix representation of the information flows. As a study, we have developed an AI-based process for the dynamic range allowance amongst multiple mobile network drivers. The intelligent abilities of the suggested workflow are given by the deep recurrent neural network based on the long short-term memory style. Simulations results show that the proposed smart model provides a steady service high quality for end users despite the offering drivers and outshines the semi-intelligent and fixed models.
Source link: https://doi.org/10.1007/978-3-030-92435-5_19
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