International Trade Balance Algorithm Based on the Ownership Principle of Mobile Edge Computing

• Main Author: Fangfang Du
• Format: Article
• Language: English
• Published: Hindawi Limited 2021-01-01
• Series: Mathematical Problems in Engineering
• Online Access: http://dx.doi.org/10.1155/2021/5569833

As an emerging mobile computing technology, mobile edge computing is an important key technology to improve the computing services of mobile devices. This paper mainly studies the balance of international trade algorithm based on the principle of moving edge computing ownership. In order to obtain all the data needed to perform the task, each mobile device can exchange data information with its connected base station through the wireless network. On the basis of satisfying the quality of service of users, including considering the user connection and service configuration, the network energy consumption is minimized in continuous t period by shutting down some servers whose resources are not fully utilized. At the same time, in order to reduce the switching cost of edge server and ensure the stability of service, frequent switching of edge server should be avoided. At the beginning, there is division of labor economy. With the development of specialized production, the degree of international division of labor is increasing due to the effect of experience accumulation. The trade efficiency is growing endogenously. The international division of labor is further deepened, and the types and quantity of products participating in the international division of labor are greatly increased, so as to realize the upgrading of trade structure. Before constructing the structural VAR model of Bti, R/W, K/L, and TFP, we need to test its stationarity. Using Eviews 5.0 software, ADF test and PP test were carried out on the unit root of BTI, r/w, K/L, and TFP time series data. With the increase of user task arrival rate, the average time revenue increases continuously. However, when the arrival rate is greater than 3 kbit/slot, the average time revenue increases slowly. The results show that the research results in system model and resource optimization algorithm will provide reliable theoretical and technical support for the practical application of mobile edge computing.