Abstract

The rich resources, virtualization, and pay-as-you-go method of cloud environment assure solutions to large-scale scientific cloud transactions. Many applications that are moving to the cloud demands both functional and temporal correctness. For profit-driven Infrastructure-as-a-Service (IaaS) cloud providers, minimizing the execution time (or makespan) and monetary cost while scheduling real-time tasks is a significant concern. However, acknowledging the complexity of resource configuration, deployment, and provisioning in the cloud environment, the existing task scheduling strategies have limited uses to address the said concern. In this regard, this work presents an algorithm that focuses on optimizing the execution time and execution cost incurred while running the real-time tasks in a cloud environment. The simulation results signify the effectiveness and applicability of the proposed approach for real-time task scheduling in the cloud environment.

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