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Berral, J.L., Fito, J.O., Julia, F., Nou, R., Guitart, J., Gavalda, R. and Torres, J. (2012) Energy-Efficient and Multifaceted Resource Management for Profit-Driven Virtualized Data Centers. Future Generation of Computer Systems, 28, 718-731.
http://dx.doi.org/10.1016/j.future.2011.12.002

has been cited by the following article:

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

  AUTHORS: Suma Sira Jacob, C. Kezi Selva Vijila

  KEYWORDS: Energy Efficiency, Power Management, Task Scheduling, Virtual Machine, Processor Architecture

  JOURNAL NAME: Circuits and Systems, Vol.7 No.8, June 22, 2016

  ABSTRACT: 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.