영문내용
(English Abstract) |
In this research work, we have focused on solving the energy management for the access points (APs) and the base stations (BSs) by introducing the temporal energy demand extrapolation model for mobile edge (ME). The goal is to fulfill the energy demand based on the task load of mobile edge servers from the smart grid. More incisively, we have modeled an extrapolation architecture for temporal energy demand prediction. Therefore, this model analyzes the heterogeneous tasks request information for extracting the energy features from the task load of the APs. Additionally, the temporal energy demand approach applies long short-term memory (LSTM) model for demand extrapolation and also, the objective is to minimize the root mean square error (RMSE). Finally, we have simulated the result of the proposed temporal energy demand extrapolation for mobile edge and we have achieved a higher degree of performance gain for the proposed model in respect to energy demand extrapolation, loss convergence, and RMSE.
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