Scheduling Workflow in Cloud Computing Based on Ant Colony Optimization Algorithm

Cloud computing environments facilitate applications by providing virtualized resources that can be provisioned dynamically. So how to schedule applications to cloud resources and the execution time should be taken into account. In this paper, we propose a scheduling strategy based on ant colony optimization (ACO) and two-way ants mechanism is introduced. Setting the pheromone threshold is to avoid the premature phenomenon, in addition, taking a two-tier search strategy and introducing pre-execution time is to avoid the local optimum so that tasks can be assigned to highest efficient computing resources. The simulation results show that the algorithm can greatly shorten the time to find the computing resource in cloud computing environment and significantly improve the efficiency.