Workflow Task Scheduling Algorithm Based on IFCM and IACO

Abstract

To solve the scheduling problem of workflow tasks in cloud computing, this paper combined the improved fuzzy c-means clustering algorithm (IFCM) and the improved ant colony optimization algorithm (IACO) and proposed a new workflow task scheduling algorithm. Firstly, the proposed algorithm used the IFCM to classify resources. Then, tasks will be sorted by their priority. Based on the results of resource clustering and the distance between resources and expect of tasks, tasks will be assigned to the appropriate resources and the scheduling will be initialized. After that, the workflow tasks will be encoded based on the initial scheduling. At last, ant colony optimization algorithm will be improved by the cross and mutation operation in genetic algorithm and used to search optimal schedules. The experiments showed that the proposed algorithm could quickly and efficiently find appropriate scheduling scheme, effectively reduce the time span of workflow tasks and increase the utilization of resources.