PWSA3C: Prioritized Workflow Scheduler in Cloud Computing Using Asynchronous Advantage Actor Critic (A3C) Algorithm

Scheduling of workflows is a critical issue in cloud computing paradigm as dynamic workflows with variable dependencies arises from heterogeneous resources which comes onto cloud application console. Mapping all these interdependent tasks to precise virtual resources is still a challenge for cloud service provider (CSP) as workflows arises to cloud application console varied from time to time with different running time capacities, dependencies, length of tasks. Ineffective scheduling of workflows creates challenges for CSP, cloud users by delaying execution of tasks, increase in rate of failures, underutilization of resources. Many earlier authors proposed various workflow scheduling mechanisms with different metaheuristic optimization approaches but generating schedules in cloud computing is a NP-hard problem and they may suffer when huge workloads coming onto cloud paradigm. Therefore, to handle the above said concerns in cloud paradigm, authors in this research proposed a prioritized workflow scheduler by Asynchronous Advantage Actor Critic (PWSA3C) algorithm by considering priorities of interdependent tasks, number of dependencies to schedule workflows to precise VMs. Extensive simulations for proposed PWSA3C algorithm conducted using workflowsim. Input to proposed approach was given with scientific workflows named Epigenomics, LIGO. For evaluating robustness of proposed PWSA3C, we compared our approach with DQN, A2C, MOABCQ algorithms. From simulated results, it is evident that PWSA3C outperformed over DQN, A2C, MOABCQ algorithms for makespan, rate of failures, utilization of resources, scalability efficiency with Epigenomics, LIGO workflows.