Optimizing Energy Consumption for Cloud Computing
Jyoti Prakash Singh, Jingchao Chen · 2019
The increased use of IT technologies and number of IT users have triggered cloud computing resource demand including the need for more data centers. Each data center consumes electricity for its un-interrupted operations and maintenance, therefore responsible for the emissions of carbon dioxide, a potent greenhouse gas causing climate change. Hence, there is a necessity to provide a solution through which energy consumption for cloud data centers can be reduced. As virtual machine located in data center are run under loaded to maintain higher performance but it causes wastage of resources and power. While, task overloading severally reduce the performance of data center. To address this issue, we propose CMBA (Cluster and Migration Based Approach) for cloud resource allocation that maps groups of tasks to customized virtual machine types based on processing, memory and network requirements. Proper placement of workload with specific VMs and dynamic migration concept reduce energy consumption for running physical machine and its respective host or data centers. Taking altogether, intelligent customization of virtual machines by adopting CMBA approach will maintain high efficiency of datacenters with reduced energy consumption.