Research on Task Scheduling Strategy Optimization Based onACO in Cloud Computing Environment
Zhenxiang He, Jiankang Dong, Zhengjiang Li, Wenjuan Guo · 2020 IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC) · 2020
Cloud computing, as a general IT service model, effectively schedules various types of request, which is very important in terms of saving resources, improving the service quality and response speed of cloud data centers. For this purpose, the cloudlet scheduling strategy of the cloud data center is studied based on the tasks sent by users as the granularity to economize the amount of virtual machines, while taking the overall work execution time into consideration. First, the principle of ACO(Ant Colony algorithm), the main process and steps of the algorithm are introduced; secondly, the scheduling strategy aiming at reducing virtual machines and task make-span is introduced. The method in this paper makes use of the advantages of ACO. By lessening running virtual machines, the data center resource utilization is improved, while taking into account the service quality of task execution time. Experiments on CloudSim have proved the effectiveness of the algorithm. Compared with traditional Greedy algorithms, it makes large decrease on virtual machine amount, lower the cost of the data center, and find a balance on make-span and service quality as well.