The week's pick
Reseach Article
Cost Effective Data Center and its Implementation in Industry
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 151 - Number 7 |
| Year of Publication: 2016 |
| Authors: Ahmed Mateen, Zulifqar Ali, Salman Afsar Awan |
10.5120/ijca2016911704
|
Ahmed Mateen, Zulifqar Ali, Salman Afsar Awan . Cost Effective Data Center and its Implementation in Industry. International Journal of Computer Applications. 151, 7 ( Oct 2016), 15-21. DOI=10.5120/ijca2016911704
Abstract
A data Centre is a dedicated space where companies can keep and operate most of the ICT infrastructure that supports their business. A server cultivate much of the time requires expansive redundant or fortification control supply structures, cooling structures, abundance frameworks organization affiliations and methodology based security systems for running the endeavor's middle applications. This would be the servers and capacity gear that run application programming and process and store information and substance. For a few organizations this may be a basic enclosure or rack of gear, for others it could be a room lodging a couple or numerous cupboards, contingent upon the size of their operation. it divided the research in to two phases in first Phase it would be analyzed the current data center infrastructure which includes energy cost, SLA (Service Level Agreement) cost, Hardware cost, maintains cost. In second phase it is suggested how to reduce electricity cost, how to control heating in data centers, how to utilize hardware at its maximum level. It also provided better solution for security, redundancy and updation. CFD modeling tool is use for analyzing data center on generated physical test bed. Both types of analysis (qualitative and quantitative).
References
- Aamodt, A., and Plaza, E., 2011. Case-Based Reasoning, Advanced Micro Devices, Artificial Intelligence Communications, 7(1): 39-59.
- Ashrae, M., and Nelson, M., 2012. Thermal Guidelines for Data Processing Environments Mission Critical Facilities. American Society of Heating, Refrigerating, and Air- Applications, 16(6): 2–45.
- Basil, Y., 2012. Energy-Efficient Data Centers: A Close-Coupled Row Solution, International Journal of Computer Sciences (IJCSI) Journal of simulation model for Wireless technology, 2(5): 2-3.
- Bauer, R., 2011. Key Issues of a Formally Based Process Model for Security Engineering, In: Sixteenth International Conference "Software & Systems Engineering & Their, 15(2): 365–371.
- Bean, J., K. Dunlap, 2012. Energy-Efficient Data Centers: A Close-Coupled Row Solution, Computer Communication Review, 19(2): 32-48.
- Chen, A., Coskun, K., and Caramanis, M., 2013. Real-time power control of data centers for providing regulation service. In Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on, 16(6): 2–4.
- Chen, M., Caramanis, C., and Coskun, K., 2014. The data center as a grid load stabilizer. In Design Automation Conference (ASP-DAC), 2014 19th Asia and South Pacific, 56(24): 105–112.
- Chiu, C., Stewart, A., and McManus, B., 2012. Electric grid balancing through low cost workload migration. SIGMETRICS Performance Evaluation Review, 40(3): 48–52.
- Daim, S., Justice, J., and Krampits, M., 2011. Consumption in Data Centers, IEEE Communications Surveys& Tutorials, 11(02): 345-876.
- Dhiman, T., Marchetti, G., and Rosing, T., 2009. A system for energy efficient computing in virtualized environments. In Proceedings of the 14th ACM/IEEE international symposium on Low power electronics and design (ISLPED), 32(12): 243–248.
- Elisa, P., Johnson, C., and Colby, W., 2011. Comparitive study of WLAN Wrox Suite, Computer Communication Review, 19(2): 32-48.
- Feldhaus, F., Freitag, S., and El Amrani, C., 2011. State-of-the-ArtTechnologies for Large-Scale Computing, Large-Scale Computing Techniques for Complex System Simulations,Wiley-IEEE Computer Society, 16(5): 1 –8.
- Gandhi, M., Balter, H., and Kozuch, A., 2012. Are sleep states effective in data centers? In IEEE IGCC, 12(6): 1–10.
- Ghatikar, W., Ganti, V., Matson, N., and Piette, M. A., 2012. Demand response opportunities and enabling technologies for data centers: Findings from field studies. 34(12):45-87.
- Hankendi, E., Reda, S., and Coskun, A. K., 2013. Adaptive power capping for virtualized servers. IEEE In ISLPED, 40(5): 415–420.
- Kant, K., 2013. Data Center Evolution A tutorial on state of the art issues and challenges, Computer Networks, 53(34): 345-543.
- Kumar, V., Talwar, P., Ranganathan, M., and Schwan, K., 2012. Coordinated management virtualized systems. Media Traffic, Journal of organizational Computing and Election Commerce, 15(4): 100-121.
- Lin, Z., Wierman, A., and Andrew, L., 2012. Online algorithms for geographical load balancing. In IEEE IGCC, 8(4): 1–10.
- Mell, P., and Grance, T., 2011. The NIST Definition of Cloud Computing‖, National Institute of Standards and Technology, Information Technology Laboratory, 15(2) 365–371.
- Mohammad, A., Talaat, A., Magdi, A., and Hoda, S., 2013, Congestion Control for Internet Newsletter, 31(4): 45-78.
- Zhenhuan, G., Xiaohui, G., and Wilkes, J., 2010. Predictive elastic resource scaling for cloud systems. In International Conference on Network and Service Management, 34(6): 9-16.
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