Abstract
Network slicing is a promising solution to satisfy different service quality requirements in the satellite-UAV integrated network of B5G and 6G. To relieve the significant transmission delay and system overhead during network slicing, we propose an auction-based distributed network slicing scheme (ADNSS), in which the resource allocation is collaboratively performed by satellite heads using an auction algorithm without transmitting the messages to the ground station in a centralized way. The convergence and service delay performance of ADNSS is analyzed in this paper. Moreover, considering that the deviation of theoretical slice analysis models from actual ones may lead to the degradation of service delay performance of ADNSS, we design an online optimization method driven by the multi-arm bandit algorithm (ORLOM) to enhance the accuracy of slice models of ADNSS in the actual environment. Numerical results show that we can achieve optimal service delay performance by ADNSS applying ORLOM after finite slicing windows and realize 8% performance improvement compared with ADNSS without ORLOM when the service number is 9. In addition, ADNSS can reduce the system overhead by 8.5%–76% compared with the centralized method in the scenario where the hops count from satellite heads to the ground station exceeds that between satellite heads by 3. As the hops count difference and service number increase, ADNSS shows more significant advantages in reducing service delay and system overhead.
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