CAJ | 학술논문

云环境下的工作流，进行合理的任务调度，可以克服地理限制，节省资源，从而提高用户的满意度。本文提出改进算法：快速非支配排序贝叶斯算法NSGAboa，该算法是快速非支配排序算法NSGAII和贝叶斯算法BOA的结合，根据种群中个体间的分布收敛程度来改变产生个体的方法，利用了种群个体信息和全局信息。实验证明该算法使得最优解的分布更加均匀，加快了个体产生的速度，缩短了种群的收敛速度。
운배경하적공작류，진행합리적임무조도，가이극복지리한제，절성자원，종이제고용호적만의도。본문제출개진산법：쾌속비지배배서패협사산법NSGAboa，해산법시쾌속비지배배서산법NSGAII화패협사산법BOA적결합，근거충군중개체간적분포수렴정도래개변산생개체적방법，이용료충군개체신식화전국신식。실험증명해산법사득최우해적분포경가균균，가쾌료개체산생적속도，축단료충군적수렴속도。
The workflow reasonable scheduling in the cloud environment, which has the ability to improve user satisfaction, can overcome geographical restrictions and saving resources. The article process a new algorithm:NSGAboa. the NSGAboa algorithm is a union of the fast nondominated sorting algorithm and Bayesian algorithm. NSGAboa algorithm, based on the degree of convergence of the distribution of the population among individuals changes the methods of generating solution individuals. The algorithm takes full advantage of the individual information of the populations and global information. Experiments show that this approach allows a more uniform distribution of the optimal solution, and reduces the convergence rate of population.