Network System Structure Design for Data Centers in Large Enterprises Using Cloud Computing

Network System Structure Design for Data Centers in Large Enterprises Using Cloud Computing

Yongfang Chi (School of Internet Application, Shenyang City University, Shenyang, China)
Copyright: © 2018 |Pages: 11
DOI: 10.4018/IJEIS.2018040106

Abstract

In this article, the author discusses the network system structure design for data centers in large enterprises using cloud computing. First, she designs a framework for a cloud data center in large enterprise systems. Second, she establishes the data center network frame based on software-defined networking (SDN) and the algorithm procedure. Third, she studies the moving algorithm of a virtual machine and the broadband allocation mechanism of a data center of a large enterprise network system along with the mathematical model. Finally, the author carries out the performance simulation analysis of the data center based on cloud computing. Finally, she carries out the performance comparison between the new data center at a large enterprise network system and traditional systems. The author shows that the new data center model in large enterprise network systems has a better network capacity and fault tolerance.
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2. Literature Review

In recent years, network system for data center of large enterprise under cloud computing environment has been concerned by many scientists, and some excellent achievements are obtained. The pulse diagnosis information was constructed, and the sensor for real-time detection is used to transmit data to data center of large enterprise based on wireless network (Yaser et al., 2014; Liu et al., 2016; Khanna et al., 2014; Bista et al., 2014; Teófilo et al., 2017). The dynamic load balancing method of cloud center based on SDN was put forward, the whole allocation of network resources and correction are completed by controller when the system is imbalanced, simulation results show that system throughput is improve (Wang Yong and Kuang Yuwen, 2015; Lu et al., 2016; Son et al., 2017; Alhazmi et al., 2017). The intelligent highway data center of large enterprise was constructed for reducing the information cost and raising the IT efficiency, and the design and implementation of server virtualization, network virtualization and storage virtualization were illustrated in detail, simulation results showed that the new method can improve the quality of data center of large enterprise effectively (Lu, 2013; Hwang et al., 2016; LeeGoodwin, 2006; Bala et al., 2009; Bahador et al., 2018). The SLA-based cloud-computing framework to facilitate resource allocation considering the workload and geographical location of distributed data centers was proposed, and empirical results show that the proposed WLARA performs better than other related approaches and using the automated SLA negotiation mechanism supports providers in earning higher profits (Son et al., 2013; Wu et al., 2014; Kertesz et al., 2014; Blesson & Rajkumar, 2018). The neuron-fuzzy inference-based prediction scheme to choose one of multiple data centers in accordance with application workloads was proposed. The new method predicts not only the present load but also the future load of data centers in the process of determining a suitable data center. And experimental results showed that our scheme was superior to other selection schemes with regard to the entire and changed loads of data centers (Gil J.M. et al., 2013; Sylvia S., 2017; Mohammad et al., 2017; Torsten, 2016; Einollah et al., 2017). This research can improve the performance of data center of large enterprise under cloud computing environment through introducing the new algorithm.

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