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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Iglesias, J.O. Stokes, N. Ventresque, A. Murphy, L. Thorburn, J. |
| Copyright Year | 2013 |
| Description | Author affiliation: IBM software Group, Toronto, ON, Canada (Thorburn, J.) || Sch. of Comput. Sci. & Inf., Univ. Coll. Dublin, Dublin, Ireland (Iglesias, J.O.; Stokes, N.; Ventresque, A.; Murphy, L.) |
| Abstract | In a heterogeneous cloud environment, the manual grading of computing assets is the first step in the process of configuring IT infrastructures to ensure optimal utilization of resources. Grading the efficiency of computing assets is however, a difficult, subjective and time consuming manual task. Thus, an automatic efficiency grading algorithm is highly desirable. In this paper, we compare the effectiveness of the different criteria used in the manual grading task for automatically determining the efficiency grading of a computing asset. We report results on a dataset of 1,200 assets from two different data centers in IBM Toronto. Our preliminary results show that electrical costs (associated with power and cooling) appear to be even more informative than hardware and age based criteria as a means of determining the efficiency grade of an asset. Our analysis also indicates that the effectiveness of the various efficiency criteria is dependent on the asset demographic of the data centre under consideration. |
| Starting Page | 974 |
| Ending Page | 975 |
| File Size | 183821 |
| Page Count | 2 |
| File Format | |
| ISSN | 21596190 |
| e-ISBN | 9780769550282 |
| DOI | 10.1109/CLOUD.2013.136 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-06-28 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Asset Utilization cost Accuracy Cooling Random access memory Manuals Hardware Workstations Arrays Asset Efficiency Grading |
| Content Type | Text |
| Resource Type | Article |
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