%0 Journal Article %1 noauthororeditor %A Bliedy, Doaa %D 2018 %J International Journal of Computer Science, Engineering and Applications (IJCSEA) %K algorithms networks %N 04 %P 47-62 %R 10.5121/ijcsea.2018.8404 %T DATACENTRE TOTAL COST OF OWNERSHIP (TCO) MODELS: A SURVEY %U http://aircconline.com/ijcsea/V8N4/8418ijcsea04.pdf %V 08 %X Datacenter total cost of ownerships (TCO) tools and spreadsheets can be used to estimate the capital and operational costs required for running datacenters. These tools are helpful for business owners to improve and evaluate the costs and the underlying efficiency of such facilities or evaluate the costs of alternatives, such as off-site computing. Well understanding of the cost drivers of TCO models can provide more opportunities to business owners to control costs .In addition, they also introduce an analytical structure in which anecdotal information can be cross-checked for consistency with other well-known parameters driving data center costs. This work focuses on comparing between number of proposed tools and spreadsheets which are publicly available to calculate datacenter total cost of ownership (TCO) ,The comparison is based on many aspects such as what are the parameters included and not included in such tools and whether the tools are documented or not. Such an approach presents a solid ground for designing more and better tools and spreadsheets in the future.

@article{noauthororeditor, abstract = {Datacenter total cost of ownerships (TCO) tools and spreadsheets can be used to estimate the capital and operational costs required for running datacenters. These tools are helpful for business owners to improve and evaluate the costs and the underlying efficiency of such facilities or evaluate the costs of alternatives, such as off-site computing. Well understanding of the cost drivers of TCO models can provide more opportunities to business owners to control costs .In addition, they also introduce an analytical structure in which anecdotal information can be cross-checked for consistency with other well-known parameters driving data center costs. This work focuses on comparing between number of proposed tools and spreadsheets which are publicly available to calculate datacenter total cost of ownership (TCO) ,The comparison is based on many aspects such as what are the parameters included and not included in such tools and whether the tools are documented or not. Such an approach presents a solid ground for designing more and better tools and spreadsheets in the future.}, added-at = {2018-09-10T14:35:30.000+0200}, author = {Bliedy, Doaa}, biburl = {https://www.bibsonomy.org/bibtex/2c43e4a3f432ba154c54ce6ae2b5c2c9f/ijcsea}, doi = {10.5121/ijcsea.2018.8404}, interhash = {6c40528af630a1389c235212724daa89}, intrahash = {c43e4a3f432ba154c54ce6ae2b5c2c9f}, issn = {2230 - 9616}, journal = {International Journal of Computer Science, Engineering and Applications (IJCSEA)}, keywords = {algorithms networks}, month = {August}, number = 04, pages = {47-62}, timestamp = {2018-09-10T14:35:30.000+0200}, title = {DATACENTRE TOTAL COST OF OWNERSHIP (TCO) MODELS: A SURVEY}, url = {http://aircconline.com/ijcsea/V8N4/8418ijcsea04.pdf}, volume = 08, year = 2018 }