A Fuzzy Approach to Evaluate Data Colocation Centers
Keywords:
Data colocation, Data center, Fuzzy set, Fuzzy operations, implication operationAbstract
We are living in the era of information technology where data is generated at enormous rate and every modern business needs their data to be stored and managed efficiently. Big corporations and government organization have enough resources to create and manage in-house data center while others may choose to rent the services from a data colocation center. A data colocation center basically provides IT related rental services to companies that required services like bandwidth, technologies, spaces etc. Colocation centers provide business with an efficient way to expand processing capabilities and grow their facilities without building everything from the ground up. Selecting data colocation provider not only increases prospect of additional flexibility and business value but also some potential risk. There are many data colocation service provider available and to choose the best one is not an easy task. In this research I have proposed an approach using fuzzy set theory to evaluate the data colocation centers. I have judged the colocation center on different criteria and used fuzzy sets to reach the decision. The fuzzy set theory gives the flexibility to express the expert opinion in linguistic terms, these linguistic terms has been assigned to some degree which can be evaluated by fuzzy set theory to conclude decision.
Downloads
References
Wierman, A., Liu, Z., Liu, I., & Mohsenian-Rad, H. (2014). Opportunities and challenges for data center demand response. Paper presented at the International Green Computing Conference.
Shuja, J., Bilal, K., Madani, S. A., & Khan, S. U
(2014). Data center energy efficient resource scheduling. Cluster Computing, 17(4), 1265-1277.
Greenberg, A., Hamilton, J., Maltz, D. A., & Patel, P. (2008). The cost of a cloud: research problems in data center networks. ACM SIGCOMM computer communication review, 39(1), 68-73.
G. Ghatikar, V. Ganti, N. E. Matson, M. A. Piette, "Demand Response Opportunities and Enabling Technologies for Data Centers: Findings from Field Studies", 2012.
Filani, D., He, J., Gao, S., Rajappa, M., Kumar, A., Shah, P., & Nagappan, R. (2008). Dynamic data center power management: Trends, issues, and solutions. Intel Technology Journal, 12(1).
Greenberg, A., Hamilton, J., Maltz, D. A., & Patel, P. (2008). The cost of a cloud: research problems in data center networks. ACM SIGCOMM computer communication review, 39(1), 68-73.
Islam, M. A., Mahmud, H., Ren, S., & Wang, X. (2015). Paying to save: Reducing cost of colocation data center via rewards. Paper presented at the 2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA).
Sun, Q., Wu, C., Ren, S., & Li, Z. (2015). Fair rewarding in colocation data centers: Truthful mechanism for emergency demand response. Paper presented at the 2015 IEEE 23rd International Symposium on Quality of Service (IWQoS).
Zhang, L., Ren, S., Wu, C., & Li, Z. (2015). A truthful incentive mechanism for emergency demand response in colocation data centers. Paper presented at the 2015 IEEE Conference on Computer Communications (INFOCOM).
"Colocation Market - Worldwide Market Forecast and Analysis (2013–2018)", [online] Available: http://www.marketsandmarkets.com/Market-Reports/colocation-market-1252.html.
"Pricing Data Center Co-location Services", 2009, [online] Available: http://enaxisconsulting.com.
J. Novet, Colocation providers customers trade tips on energy savings, Nov.2013, [online] Available: http://www.datacenterknowledge.com/.
L. A. Zadeh, Fuzzy Sets, Information and Control 8 (1965) 338-353.
Kaufmann and M.M. Gupta, Introduction to Fuzzy Arithmetic Theory and Applications (Van Nostrand Reinhold, New York, 1991).
Kaufmann: Introduction to the Theory of Fuzzy Subsets, Vol. I, Academic Press, New York, 1974.
H.-J. Zimmermann, Fuzzy Set Theory and It's Applications, Second Revised Edition.
Zadeh, L.A., “Fuzzy Logic,” Computer, Vol. 1, No. 4, pp. 83-93, 1988.
Zadeh, L.A., “Knowledge representation in fuzzy logic,” IEEE Transactions on Knowledge and Data Engineering, Vol. 1, pp. 89-100, 1989.
"Colocation Data center ABC", HubSpot, [online] Available: https://cdn2.hubspot.net › hubfs › PP_Colocation Data Center ABC.
Akinola, Ayotuyi, “Performance Evaluation of Data Center Network Setup Architectures”, (2017).
Dubois, D., & Prade, H. (1978). Operations on fuzzy numbers. International Journal of systems science, 9(6), 613-626.
Karnik, N. N., & Mendel, J. M. (2001). Operations on type-2 fuzzy sets. Fuzzy sets and systems, 122(2), 327-348.
Mizumoto, M. (1981). Fuzzy sets and their operations, II. Information and control, 50(2), 160-174.
Mas M, Monserrat M, Torrens J, Trillas E. A survey on fuzzy implication functions. IEEE Transactions on fuzzy systems. 2007 Dec 6;15(6):1107-21.
M. Baczyński, B. Jayaram (2007) On the characterization of (S,N)-implications Fuzzy Sets Syst., 158 (2007), pp. 1713-1727
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
