Abstract

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.

Highlights

  • Since the reform and opening up, China has achieved high-quality development in all economic fields

  • When the task is processed locally, the energy consumption has nothing to do with the channel transmission rate, and the local processing energy consumption appears as a horizontal straight line

  • As the channel transmission rate increases, the energy consumption curve of the PD-BPSO algorithm and the greedy algorithm decreases. is is because the higher the channel transmission rate, the shorter the time spent on data transmission

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Summary

Introduction

Since the reform and opening up, China has achieved high-quality development in all economic fields. Even after the subprime mortgage crisis in the United States, China’s economy has maintained a stable and rapid development, and its GDP growth rate ranks first in the world [1] In this background, in order to meet the requirements of wireless data transmission and mobile devices to solve the problems [2], this article will research on the edge of the mobile computing network weighted bits and maximize and safety calculation efficiency maximization problem, so as to further enhance the security of the mobile computing performance and energy efficiency. Lin C J believes that the next-generation mobile network 5G aims to support lower end-to-end latency, higher reliability, and higher throughput, which can be improved by MEC and multi-RAT offloading, respectively He introduced a dual offloading mechanism called LCCOP, which offloads incoming traffic to the best wireless pair and edge pair, depending on the end-to-end latency of the request connection. Cross-section data of each country are adopted, and the combination of time series and cross-section can more scientifically explain the impact of RMB exchange rate fluctuations on the trade balance between China and various trading partners

Ownership Principle of Mobile Edge Computing
Mobile Edge Computing Algorithm Simulation
Model Simulation Results
Conclusions
Full Text
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