Calculation unloading method based on hybrid genetic algorithm in mobile edge calculation

Abstract

The invention discloses a hybrid genetic algorithm-based calculation unloading method in mobile edge calculation, which comprises the following steps: S1, establishing a system model to obtain calculation time delay of a sub-task set in each processor and transmission time delay among the processors, and determining each task layer value in the sub-task set according to a constraint relationship of the sub-task set; S2, initializing a population according to the determined task layer value and a random strategy to obtain initial population individuals of the sub-task set, performing symbol coding to obtain a task scheduling sequence, and optimizing the individuals in the initial population; S3, constructing a fitness evaluation function, and performing selection operation on individuals inthe optimized initial population; S4, constructing a crossover mechanism, and crossover individuals in the new population by using crossover operation based on a tabu table search algorithm; S5, performing mutation operation on individuals in the new population by using mutation operation based on a simulated annealing algorithm; and S6, judging whether the iteration step length is reached or not, and if not, repeating the step S3-S5; and if so, outputting a globally optimal solution.

Description

technical field [0001] The present invention relates to the field of mobile edge technology, in particular to a computing offloading method based on a hybrid genetic algorithm in mobile edge computing. Background technique [0002] With the development of the Internet of Things (IoT), there is a new wave of mobile user equipment (UE) such as smartphones and laptops. It is difficult for traditional applications to meet the growing needs of IoT-based users, such as quality of service. Recently, many novel applications have emerged and are quickly favored by users, such as real-time online games, virtual reality, etc. [0003] Although the processing power of today's mobile devices is getting stronger and stronger, mobile devices usually have limited battery capacity and cannot handle huge applications in a short period of time, which has become a bottleneck for the future development of mobile applications. Strict latency constraints have become an obstacle to running comple...

AI Technical Summary

Problems solved by technology

Although the data processing speed is fast, the network bandwidth is very limited

As data continues to increase, data transmission speed has become a bottleneck for improving cloud computing capabilities

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