Bi-Criteria Priority based Particle Swarm Optimization workflow scheduling algorithm for cloud

Cloud Computing is based upon market oriented business model in which users can access the cloud services through Internet and pay only for what they use. Large scale scientific applications are often expressed as Workflows. Workflow tasks should be scheduled efficiently such that execution time as well as cost incurred by using a set of heterogeneous resources over cloud should be minimized. In this paper, we propose Bi-Criteria Priority based Particle Swarm Optimization (BPSO) to schedule workflow tasks over the available cloud resources that minimized the execution cost and the execution time under given the deadline and budget constraints. The proposed algorithm is evaluated using simulation with four different real world workflow applications and comparison is done with Budget Constrained Heterogeneous Earliest Finish Time (BHEFT) and standard PSO. The simulation results show that our scheduling algorithm significantly decreasing the execution cost of schedule as compared to BHEFT and PSO under the same Deadline and Budget Constraint and using same pricing model.