A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments
Cloud computing environments facilitate applications by providing virtualized resources that can be provisioned dynamically. However, users are charged on a pay-per-use basis. User applications may incur large data retrieval and execution costs when they are scheduled taking into account only the 'Execution time'. In addition to optimizing execution time, the cost arising from data transfers between resources as well as execution costs must also be taken into account. In this paper, the authors present a Particle Swarm Optimization (PSO) based heuristic to schedule applications to cloud resources that takes into account both computation cost and data transmission cost.