Abstract:
In the report, in order to solve the multi-criteria optimal scheduling problem of workflow with data constraints, a data-aware scheduling algorithm based on business logic and considering data constraints was proposed. Workflow scheduling was modeled as a multi-objective optimization problem, a data-aware ant colony algorithm (DACO) was developed to search the optimal scheduling method, the amount of data required for each task and the data constraints between tasks were determined, the data flow between each business was perceived, and then, the divide-and-conquer strategy to search the optimal scheduling. The results showed that the algorithm is superior to the existing methods in terms of efficiency and cost-effectiveness.