James, Jason2012-06-282012-06-282012-06-28https://hdl.handle.net/1794/12234This paper was completed as part of the final research component in the University of Oregon Applied Information Management Master's Degree Program [see htpp://aim.uoregon.edu].This annotated bibliography reviews literature published between 2008 and 2011 to identify the potential for cloud computing to lower power consumption and reduce carbon emissions. Accounting for varied energy efficiency factors (location, virtualization, architectural design, and management systems), cloud providers implementing carbon/energy based scheduling policies can achieve energy savings in comparison to profit based scheduling policies, leading to higher profit and less carbon emissions (Garg, S., Yeo, C., Anandasivam, A., & Buyya, R. 2011).en-USrights_reservedApplied Information ManagementAIMDataCapstoneOther