Cloud Computing Task Scheduling Method Based on Improved Genetic Algorithm
There may be a large number of computing nodes and uncertain factors in the cloud computing environment,requiring large-scale task scheduling and management,which increases the complexity and difficulty of scheduling.In order to meet the real-time re-quirements of task scheduling and reduce energy consumption during the process,a cloud computing task scheduling method based on im-proved genetic algorithm is proposed.Combine different task attributes,reset the task attributes of each cloud computing node,and calculate the comprehensive attribute values of the nodes.Based on the calculation results,a cloud computing task scheduling model is constructed with the goal of minimizing the completion time of all tasks.The traditional genetic algorithm is improved to optimize the initial formation mode of the population,and the scheduling model is solved by the improved genetic algorithm to determine whether the obtained solution meets the termination condition.If the optimal cloud computing task scheduling scheme can be directly output,the optimized scheduling of cloud computing tasks can be realized.According to the experimental results,it can be seen that the task scheduling completion time of the proposed method is relatively low,with a maximum scheduling time of only 16 minutes.It is indicated that the proposed method can meet the real-time requirements of task scheduling and has low energy consumption,achieving efficient task execution and reasonable resource utilization.
improved genetic algorithmcloud computingtask schedulingfitnessobjective function
万方数据
维普
