Optimizing Virtual Machine Placement to Lower Energy Usage in Green Cloud Computing

Abstract

The rapid advancement of global digitization and the proliferation of web and mobile applications have significantly increased the demand for cloud-based solutions. This urge in internet users necessitates a greater number of data centers, which in turn requires substantial energy resources and results in high carbon dioxide emissions. Various strategies have been proposed to mitigate energy consumption in data centers; however, these solutions often compromise critical factors such as Quality of Service (QoS), Service Level Agreement (SLA) adherence, and overall system performance. This paper examines  proposed approaches  load-aware VM placement in green cloud computing. The methods of VM relocation, host selection, and VM migration, along with task submission and VM placement, are used for their effectiveness in reducing virtual machine migration, conserving energy, and enhancing system performance. Conversely, the overloaded/underloaded host selection method is emphasized for its role in improving system performance and maintaining SLA compliance. This systematic analysis aims to address the trade-offs inherent in existing energy-efficient strategies and propose integrated solutions for optimizing both energy use and performance in data centers.