Energy Consumption Optimization Method for Wireless Communication Data Transmission in Cloud Environment

With the development of wireless network technology, the data transmission efficiency of wireless communication has been greatly improved. The transmission of wireless communication data on the gateway device will inevitably consume device energy. Excessive energy consumption of the device will affect the quality of the communication signal. Only by reducing the energy consumption during the data transmission process can the user be provided with satisfactory communication services. This paper proposes an energy consumption optimization technology for wireless communication transmission in cloud environment from the perspective of resource deployment and task scheduling. The related algorithms include virtual machine scheduling algorithm and minimum energy scheduling algorithm. The two algorithms are used to simulate different data transmission tasks. Comparing the completion time and energy consumption of the two algorithms for different data transmission tasks, the research results show that as the data transmission volume increases, the data transmission completion time and energy consumption of the two algorithms increase, but compared with the virtual The minimum energy scheduling algorithm has a shorter completion time and less energy consumption, indicating that the minimum energy scheduling algorithm can be used to optimize the wireless data transmission system and improve the data transmission efficiency.