LEO satellite Internet resource allocation strategy based on terminal traffic prediction
A resource allocation strategy for the low earth orbit(LEO)satellite Internet based on terminal traffic predic-tion was proposed to address the problems of blind coverage spots in ground network and the low resource utilization of satellite network.An improved LSTM-ARIMA algorithm was proposed with real datasets by the strategy to accurately predict the data traffic generated in the ground area over a certain period of time in the future.Two communication mod-els,differentiated data transmission and task offloading were constructed through Stackelberg games,taking into the data processing latency and energy consumption account.By solving the Nash equilibrium,the optimal ratio for users to trans-mit data or unload tasks through the LEO satellite Internet,as well as the optimal pricing for satellites to provide network services,were obtained.Extensive simulation results verify that the proposed strategy can increase the revenue by ap-proximately 40%in data transmission services and 50%in task offloading services.
LEO satellite Internetdata flow predictionresource allocationdata transmissiontask offloading
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