Research On Task Scheduling Based On Chaotic Ant Colony Algorithm In Cloud Environment

Cloud computing emerges in the context of the rapid development of massive data processing capabilities and network technologies.The cloud packages computing power as a product offering user,and the user can obtain computing resources according to the billing mode in the cloud environment as needed.Task scheduling in the cloud environment will directly affect the operating speed and user service experience of the cloud data center.Therefore,it is very important to design a cloud task scheduling strategy that meets the needs of users and improves the user service experience.In order to optimize the scheduling performance of task scheduling in cloud environment,this paper studies the independent task scheduling in cloud environment based on the basic ant colony algorithm,and focuses on the scheduling time and scheduling cost that the user pays most attention to,and is based on the basic ant colony algorithm.On the design of the corresponding improved algorithm.First of all,under the background of scheduling independent tasks in the cloud environment,we present the model of task scheduling in the cloud environment,and then describe the commonly used task scheduling algorithms in the cloud environment.Secondly,according to the comprehensive consideration of task set scheduling time span,scheduling cost and load balancing ratio,a task scheduling strategy based on chaotic ant colony algorithm is proposed.This strategy replaces the basic ant colony algorithm with the chaotic ant colony algorithm,determines the pheromone with the remaining resource usage rate of the virtual machine node,and improves the efficiency of rational distribution of tasks to the virtual machine.Through the interaction of the ant and the neighbor,the ant is several Finding the best position amorng the optimal positions and adding the pheromone update-mode of chaotic disturbances simultaneously achieve the best solution when searching for the optimal solution,thereby improving the search accuracy of the algorithm.Finally,compared with the basic ant cotony algorithm,the experimental results show that this scheduling strategy is an effective task scheduling method in the cloud environment.It can effectively reduce the task schedule completion time and cost,and takes into account the system load balancing.