Artificial Bee Colony for workflow scheduling

Cloud computing is the provision of computing resource services from which users can obtain resources via network to tackle their demands. In recent years, with fast growing information technology, more users apply this service; as a result, the demand has increased dramatically. In addition, most of the complex tasks are represented by workflow and executed in the cloud. Therefore, as service providers face this increasing demand, how to schedule the workflow and reduce the response time becomes a critical issue. This research integrates the concept of project scheduling with the workflow scheduling problem to formulate a mathematical model, which expects to minimize the total completion time. Two Artificial Bee Colony algorithms are proposed to solve the workflow scheduling optimization problem. The performance of ABC is compared with the optimal solutions obtained by Gurobi optimizer on the instance containing different sizes of workflows. The results show that ABC can be considered a practical method for complicated workflow scheduling problems in the cloud computing environment.