MEC calculation unloading method for joint optimization of delay and energy consumption

Abstract

The invention discloses a delay and energy consumption joint optimization MEC computing unloading method, and aims to solve the problems that in computing unloading of multiple users to multiple servers of an MEC, server resources are scrambled by unloading requests of the users, optimal unloading occurs, the effective utilization rate of the resources is low, the unloading service quality is poor and the like. According to the method, delay and energy consumption serve as constraints, an unloading cost evaluation model is constructed and calculated, in order to determine an unloading target, a server selection operator is designed, a server meeting task response delay is preferentially selected to execute unloading calculation, and an improved difference algorithm with response delay, energy consumption and server load serving as fitness functions is designed; an unloading decision with a low adaptive value is searched, and low-overhead and load-balanced efficient calculation unloading is realized; simulation experiments prove that the method reduces the delay and energy consumption of the mobile edge computing network, improves the task satisfaction response delay rate, balances the load of the server, and improves the user satisfaction, energy consumption efficiency and stability of the mobile edge computing system.

Description

technical field [0001] The invention relates to the technical field of mobile edge computing, in particular to an MEC computing unloading method for joint optimization of delay and energy consumption. Background technique [0002] With the rapid arrival of the Internet of Everything era, the number of mobile smart terminals such as mobile phones and pads and network traffic data are increasing rapidly, and applications such as face recognition, automatic driving, and mobile augmented reality are becoming more and more complex. Such applications are highly time-sensitive and require large resources. As a new type of computing model, Mobile Edge Computing (MEC) responds to users' offloading requests in real time by deploying servers at the edge of the network close to users, so as to realize local and fast network services; effective Fusion scheduling resources to meet the huge and diverse computing needs is an important content of MEC research. As one of the key technologies ...

AI Technical Summary

Problems solved by technology

[0005] The present invention aims at the mobile edge computing environment, where the device types are dynamic and complex, and when multi-users unload calculations on multiple servers, they face user offloading requests to compete for server resources, leading to optimal offloading, low effective utilization of resources, and offloading service quality In order to solve the problem of poor performance, a MEC computing offloading method based on joint optimization of delay and energy consumption is provided. This method takes delay and energy consumption as constraints, establishes a calculation offl

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