智能系统学报2024，Vol.19Issue(6)：1573-1583,11.DOI:10.11992/tis.202312042
基于多群体混合智能优化算法的卸载决策寻优方法
Unloading decision optimization method based on multi-population hybrid intelligent optimization algorithm
摘要
Abstract
In the network architecture of mobile edge computing,an offloading decision controller was introduced to balance the reduction of energy consumption and delay.This controller obtains the optimal offloading decision through an offloading decision optimization algorithm.A new ABC-FS algorithm was proposed by combining the artificial bee colony(ABC)algorithm and the artificial fish swarm(FS)algorithm.Additionally,a Gaussian decay function was intro-duced to transition the algorithm parameters from static to dynamic,and the inertia weight factor of the improved particle swarm optimization algorithm was incorporated,creating a multi-population hybrid intelligent optimization al-gorithm.Finally,an objective function that jointly optimizes delay and energy consumption was designed,and simula-tion experiments were conducted using Poisson probability.Simulation results show that the proposed offloading strategy optimization algorithm achieves faster convergence speed compared to several benchmark methods and effect-ively balances the reduction of total task offloading delay and total energy consumption in multi-access edge computing scenarios.关键词
移动边缘计算/计算卸载/人工鱼群算法/人工蜂群算法/自相似排队模型/高斯衰减函数/粒子群算法/惯性权重因子Key words
moving edge computing/calculating offloading/artificial fish swarm algorithm/artificial colony algorithm/self-similar queuing model/gaussian attenuation function/particle swarm optimization/inertia weight factor分类
计算机与自动化引用本文复制引用
方浩添,田乐,郭茂祖..基于多群体混合智能优化算法的卸载决策寻优方法[J].智能系统学报,2024,19(6):1573-1583,11.基金项目
国家自然科学基金项目(62271036) （62271036）
国家重点研发计划科技冬奥重点专项(2021YFF0306303). （2021YFF0306303）
