云中截止时间动态分配的工作流调度成本优化算法.

Nowadays, how to reduce the execution cost of workflow under the premise of meeting the deadline constraint is one of the main problems of workflow scheduling in cloud. A three-step list scheduling algorithm can solve this problem effectively. However, the algorithm can only form static sub-deadline in deadline allocation stage. To provide convenience for users to deploy workflow tasks, cloud service providers provide users with three types of instances. Among them, spot instance has great price advantage and can greatly reduce the execution cost of workflow. To solve the above problems, this paper proposed a cost optimization algorithm based on dynamic allocation of deadline for workflow scheduling (S-DTDA). This algorithm used particle swarm optimization to dynamically allocate the deadline, which made up for the defect of the three-step list scheduling algorithm. In the virtual machine selection stage, the algorithm added the spot instance to the candidate resources, which greatly reduced the execution cost. Experimental results show that compared with other classical algorithms, this algorithm has obvious advantages in experimental success rate and execution cost. In conclusion, S-DTDA algorithm can effectively solve the cost optimization problem of deadline constraint in workflow scheduling. [ABSTRACT FROM AUTHOR]