Energy Aware Processor Architecture for Effective Scheduling and Power Management in Cloud Using Inclusive Power-Cognizant Processor Controller

The fast acceptance of

cloud technology to industry explains increasing energy conservation needs and

adoption of energy aware scheduling methods to cloud. Power consumption is one

of the top of mind issues in cloud, because the usage of cloud storage by the

individuals or organization grows rapidly. Developing an efficient power

management processor architecture has gained considerable attention. However,

the conventional power management mechanism fails to consider task scheduling

policies. Therefore, this work presents a novel energy aware framework for

power management. The proposed system leads to the development of Inclusive

Power-Cognizant Processor Controller (IPCPC) for efficient power utilization.

To evaluate the performance of the proposed method, simulation experiments

inputting random tasks as well as tasks collected from Google Trace Logs were

conducted to validate the supremacy of IPCPC. The research based on Real world

Google Trace Logs gives results that proposed framework leads to less than 9%

of total power consumption per task of server which proves reduction in the

overall power needed.