Lagrange-based energy consumption optimization method for computing migration terminal

Abstract

The invention discloses a Lagrange-based energy consumption optimization method for a computing migration terminal. The method takes the minimization of the total computing time and the energy consumption of a mobile terminal as a target, models a computing migration resource partitioning problem of the mobile terminal into a convex optimization problem, and constructs a multi-user MECO system forlong-term evolution application based on time division multiple access and a task migration model which migrates multiple user tasks to an edge cloud base station. In the problem of convex optimization for the multi-user computing migration energy consumption, the migration scheme is designed by taking the optimal computing time as a constraint and taking the minimization of the local energy consumption of the terminal as a target, and finally an optimal terminal resource partitioning strategy is determined. The method achieves the purposes of saving the energy consumption of the terminal andreducing the network delay so as to improve the performance of the mobile terminal to be greatest extent. Experiments show that the migration strategy model can effectively balance the relation between local computing and migration computing, thereby providing a guarantee for executing computing intensive applications in mobile edge computing.

Description

Technical field [0001] The invention relates to the technical field of mobile edge computing, in particular to a Lagrangian-based method for optimizing energy consumption of a computing migration terminal in edge computing. Background technique [0002] As smart mobile terminals are updated and upgraded, smart terminals have increasingly powerful functions. To make mobile devices smaller, lighter, and longer battery life means that their computing power will be limited. However, as users’ expectations for smart mobile terminals become higher and higher, this requires the terminal’s computing and data operation capabilities to reach a higher level, and achieving a higher level of computing and data operation capabilities is based on high energy consumption. The cost, how to coordinate this contradiction, is the current technical bottleneck in the development of smart mobile terminals. [0003] In recent years, mobile terminals such as smartphones and tablet computers are becoming ...

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Problems solved by technology

[0008] In the process of realizing the present invention, the following problems exist in the prior art: the research on MECO resource division in the prior art mainly focuses on the algorithm design, and most of them only relate to single-user MECO, and the resource division of multi-user MECO is lacking. Research

And most of them only consider the calculation delay, or only consider the terminal energy consumption, without considering the joint delay and energy consumption, it is impossible to achieve the global optimum, and it cannot effectively solve the problem of limited mobile terminal resources, especially the energy consumption. question

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