HEFT based workflow scheduling algorithm for cost optimization within deadline in hybrid clouds

Cloud computing nowadays is playing major role in storage and processing huge tasks with scalability options. Deadline based scheduling is the main focus when we process the tasks using available resources. Private cloud is owned by an organization and resources are free for user whereas public clouds charge users using pay-as-you-go model. When the private cloud is not enough for processing user tasks, resources can be acquired from public cloud. The combination of a public cloud and a private cloud gives rise to hybrid cloud. In hybrid clouds, task scheduling is a complex process as tasks can be allocated resources of either the private cloud or the public cloud. This paper presents an algorithm that decides which resources should be taken on lease from public cloud to complete the workflow execution within deadline and with minimum monetary cost for user. A hybrid scheduling algorithm has been proposed which uses a new concept of sub-deadline for rescheduling and allocation of resources in public cloud. The algorithm helps in finding best resources on public cloud for cost saving and complete workflow execution within deadlines. Three rescheduling policies have been evaluated in this paper. For performance analysis, we have compared the HEFT (Heterogeneous Earliest Finish Time) based hybrid scheduling algorithm with greedy approach and min-min approach. Results have shown that the proposed algorithm optimizes a large amount of cost compared to greedy and min-min approaches and completes all tasks within deadline.