Tolerable Data Transmission of Mobile Edge Computing Under Internet of Things

With the emergence of in-depth research of emerging technologies or 5G mobile communication technology methods, the IoT applications have been further sublimated. In this paper, the new characteristics and new challenges appearing in the current mobile edge computing are sorted out, and the latest related models and work are summarized. The important optimization models and moving models and wireless block data in mobile edge computing are analyzed and discussed. On this basis, this paper mainly designs and verifies the following three aspects of mobile edge computing. A joint optimization model of task offloading and power allocation is established, and a centralized joint optimization algorithm for task unloading and power allocation is proposed. Based on the equalization delay and the impact of energy consumption on task unloading, the algorithm can use the idle resources that can be used to distribute and unload the computing tasks. The simulation experiments show that the algorithm can not only coordinate task offloading and power allocation effectively, but also improve the balance between system delay and energy consumption. Delay-tolerable data can be modeled as a partially observable Markov decision process in a software-defined transport and compute node selection process. Compared with the existing scheme, the proposed method can effectively reduce system overhead, shorten data calculation execution time, improve data calculation efficiency, and ensure that the delay can tolerate data transmission arrival rate under the condition of transmission delay.