IFFO: An Improved Fruit Fly Optimization Algorithm for Multiple Workflow Scheduling Minimizing Cost and Makespan in Cloud Computing Environments

Cloud computing platforms have been extensively using scientific workflows to execute large-scale applications. However, multiobjective workflow scheduling with standards optimize QoS parameters is a challenging task. Various metaheuristic techniques proposed satisfy the like makespan, cost, and resource utilization. Still, traditional approaches are incompetent maintain agreeable equilibrium between exploration exploitation of search space because their limitations getting trapped in local optimum value at later evolution stages higher-dimensional nonlinear optimization problem. This paper proposes an improved Fruit Fly Optimization (IFFO) algorithm minimize makespan cost for multiple cloud environment. The evaluated CloudSim workflows. comparative results depict that IFFO outperforms FFO, PSO, GA.