An Optimized Task Submission and VM Placement method to Reduce Energy Consumption in Green Cloud Computing
Keywords:
IaaS (Infrastructure as a Service), PaaS (Platform as a Service), SaaS (Software as a Service), VM (Virtual Machine), HypervisorAbstract
In the context of cloud computing, energy consumption is a significant concern, particularly in green computing, which seeks to minimize environmental impact while maintaining high computational efficiency. This paper proposes an optimized task submission and virtual machine (VM) placement method aimed at reducing energy consumption in cloud data centers. The proposed approach integrates task scheduling with VM allocation to ensure that computational resources are used efficiently. By considering factors such as task priorities, resource requirements, and VM energy profiles, the method minimizes idle times and balances workload distribution across physical hosts. Simulation results demonstrate that the proposed technique significantly reduces energy consumption compared to traditional task submission and VM placement strategies. The approach ensures optimal resource utilization while meeting quality-of-service (QoS) requirements, offering a sustainable solution for green cloud computing environments.
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