Distributed energy management and optimization method in multi-user mobile edge computing system

Abstract

The invention relates to a distributed energy management and optimization method in a multi-user mobile edge computing system. The distributed energy management and optimization method in the multi-user mobile edge computing system comprises the following steps: modeling a system according to the characteristics of the mobile edge computing technology and the energy harvesting technology, and an energy consumption problem of a mobile device to plan a system energy management and optimization problem, and using the target of minimizing the system energy consumption as an objective function; andperforming reasonable relaxation on building the system energy management and optimization problem, using a Lyapunov optimization method to deal with the converted problem to obtain an online optimization algorithm, and further obtaining a distributed optimization algorithm by using an ADMM distributed method. The distributed energy management and optimization method in the multi-user mobile edgecomputing system can effectively reduce the energy consumption in the multi-user mobile edge computing system.

Description

technical field [0001] The present invention relates to the technical field of wireless communication, in particular to a distributed energy management optimization method in a multi-user mobile edge computing system. Background technique [0002] With the widespread use of smart mobile devices and the rapid development of the mobile Internet, more and more IoT terminal devices (smart bracelets, wireless monitoring, etc.) have been widely used in industries such as industry, agriculture, transportation, smart home, and environmental testing. . However, under the circumstances that the current mobile devices only have limited processing capabilities, and it is difficult to satisfy the user experience, how to effectively improve the current situation is undoubtedly a big challenge. Therefore, in order to effectively alleviate the computing load pressure of mobile devices, improve the quality of computing services, and meet the requirements of high-bandwidth and low-latency ne...

AI Technical Summary

Problems solved by technology

In terms of energy supply for mobile devices, batteries with limited capacity also bring a lot of inconvenience to users, and with the loss of the battery itself after use, it will also lead to a gradual decline in the ability of the battery to store power, which in turn causes Users need to recharge frequently and reduce user experience. Therefore, energy harvesting technology can be considered to alleviate energy consumption problems, and provide power for computing and communication services of mobile devices by collecting renewable energy in the environment.

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