An Energy and Performance Balancing Algorithm Based on Adaptive Cloud Resource Re-Configurability

Abstract

Due to its speedier execution and adaptable processing, cloud computing VMs with Dynamic Voltage and Frequency Scaling (DVFS) have achieved tremendous demand in real time. It can meet the major goals of high energy efficiency, resource allocation, and cloud computing VM balancing. In order to properly exploit cloud computing systems, it is important to achieve a high balance between resource allocation and reconfiguration cost in the cloud computing environment. It is vital in cloud computing systems to strike a balance between resource allocation, energy consumption, and information processing center performance, as well as decreasing job load. As a result, an Adaptive Cloud Resource Re- Configurability (ACRR) model is presented here, which relies on Dynamic Voltage and Frequency Scaling (DVFS) to reduce high reconfiguration costs in various data processing applications. Experimental results verify superiority of our proposed ACRR technique in terms of power consumption, average power and power sum.