Smart Energy Station Terminal 5G Adaptation Strategy Based on Genetic-Algorithm Task Offloading Method
Qin Li, Qi Zengqing, Lin Weiwei, XU Zhi-qiang · 2021 IEEE 21st International Conference on Communication Technology (ICCT) · 2021
In order to meet the multi-service delay and power consumption requirements of smart energy stations without local hardware upgrades, this paper proposed a terminal 5G adaptation strategy based on genetic-algorithm task offloading method for smart energy station. Firstly, the related delay and reliability requirements are analyzed for the terminal tasks the smart energy station. Then, genetic algorithms are used to consider the delay and power consumption to optimize and obtain the optimal task offloading decision. Finally, the proposed genetic-algorithm task offloading method is depicted to implement the terminal 5G adaptation in the Smart energy station. Simulation experiment results illustrate that the proposed task offloading strategy can adapt to the terminal 5G performance of the smart energy station effectively, while the decision result meets the QoS requirements of the terminal services of the smart energy station.