As a global digitization advancement, there is a massive need of cloud-based solutions and data centers. Another reason behind excessive need of data centers is because of increasing number of internet users. Increasing demand of data centers simultaneously need huge amount of energy for data center operation and on other end emit enormous amount of CO2. Several approaches have been proposed to reduce energy consumption, but major concern is by looking at one parameter or criteria they must compromise on other. Our proposed approach MIPS-Aware VM Placement in combination with searching of best capable host helps to reduce VM migration and increase mean time for better performance and save energy. Proposed approach identifies overloaded and underloaded hosts and to improve system performance algorithm does not allow to allocate additional workload, which will also help to reduce energy and get better QoS. Proposed approach significantly decreases VM migration and increase mean time before VM migration which in turns helps to reduce energy and associated cost. By using proposed MIPS-Aware VM Placement approach, we can reduce upto 25% more energy consumption compared to traditional approaches.
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An Optimized VM Placement Approach to Reduce Energy Consumption in Green Cloud Computing
Semantic Scholar · Computer Science · 2021
Abstract
As a global digitization advancement, there is a massive need of cloud-based solutions and data centers. Another reason behind excessive need of data centers is because of increasing number of internet users. Increasing demand of data centers simultaneously need huge amount of energy for data center operation and on other end emit enormous amount of CO2. Several approaches have been proposed to reduce energy consumption, but major concern is by looking at one parameter or criteria they must compromise on other. Our proposed approach MIPS-Aware VM Placement in combination with searching of best capable host helps to reduce VM migration and increase mean time for better performance and save energy. Proposed approach identifies overloaded and underloaded hosts and to improve system performance algorithm does not allow to allocate additional workload, which will also help to reduce energy and get better QoS. Proposed approach significantly decreases VM migration and increase mean time before VM migration which in turns helps to reduce energy and associated cost. By using proposed MIPS-Aware VM Placement approach, we can reduce upto 25% more energy consumption compared to traditional approaches.