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• W4327773135 abstract "Energy usage has become one of the significant concerns to help accelerate the development of the cloud computing environment because it increases the price of power exponentially to service suppliers and plays an essential role in carbon emissions and thus environmental degradation, and it harms system availability and reliability. Load balancing methods have raised concerns that efficient energy consumption and optimum resource utilization should be considered further. Towards heterogeneous ecosystems, this is an important area of concern. This research presents an efficient energy-aware load balancing (EEALB) method to improve resource utilization and total run time and reduce energy consumption. The proposed method mainly focuses on time and energy awareness. It utilizes the ant colony method for resource allocation. It reduces energy utilization and make span per the essential parameter defined by the cloud service user or provider. The experimental results demonstrate the quality of the proposed method over existing methods." @default.
• W4327773135 created "2023-03-19" @default.
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• W4327773135 date "2022-12-09" @default.
• W4327773135 modified "2023-10-16" @default.
• W4327773135 title "An Efficient Energy-Aware Load Balancing Method for Cloud Computing" @default.
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• W4327773135 doi "https://doi.org/10.1109/aist55798.2022.10064866" @default.
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