Enhanced MBFD Algorithm to Minimize Energy Consumption in Cloud
Main Article Content
Abstract
Background/Objectives: Cloud computing is a shared pool of configurable computer system resources and higher-level services. These services quickly configured over the Internet to achieve consistency and economies of scale.
Methods/Statistical analysis: In this research, the DVFS (Dynamic Voltage and Frequency Scaling) mechanism is used to save energy in the cloud environment. In the existing work, MBFD has been used to check the resources in the physical machine. In case, if the resources are available, then the VM is placed over the PM. However, the problem is that the MBFD algorithm does not check the PM and hence result in higher energy consumption.
Findings: In this paper, the MBFD algorithm is enhanced by using the concept of DVFS along with the concept of location-aware algorithm. Due to this algorithm, VM which is near to the server is executed first by measuring the distance. To measure the performance the parameters such as energy consumption and TCJ are measured.
Improvements/Applications: The proposed framework reduced energy consumption and increased the total completed jobs.
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