JACIII Vol.25 No.1 pp. 13-22
doi: 10.20965/jaciii.2021.p0013


Variable Expanding Structure for Data Center Interconnection Networks

Jianfei Zhang, Yuchen Jiang, and Yan Liu

School of Computer Science and Technology, Changchun University of Science and Technology
No.7089 Weixing Road, Changchun, Jilin 130022, China

Corresponding author

July 17, 2020
October 12, 2020
January 20, 2021
data center, interconnection network, network topology, variable expanding

Data centers are fundamental facilities that support high-performance computing and large-scale data processing. To guarantee that a data center can provide excellent properties of expanding and routing, the interconnection network of a data center should be designed elaborately. Herein, we propose a novel structure for the interconnection network of data centers that can be expanded with a variable coefficient, also known as a variable expanding structure (VES). A VES is designed in a hierarchical manner and built iteratively. A VES can include hundreds of thousands and millions of servers with only a few layers. Meanwhile, a VES has an extremely short diameter, which implies better performance on routing between every pair of servers. Furthermore, we design an address space for the servers and switches in a VES. In addition, we propose a construction algorithm and routing algorithm associated with the address space. The results and analysis of simulations verify that the expanding rate of a VES depends on three factors: n, m, and k where the n is the number of ports on a switch, the m is the expanding speed and the k is the number of layers. However, the factor m yields the optimal effect. Hence, a VES can be designed with factor m to achieve the expected expanding rate and server scale based on the initial planning objectives.

A VES<sub>k</sub> structure that consists of <i>m</i> VES<sub>k-1</sub>s

A VESk structure that consists of m VESk-1s

Cite this article as:
J. Zhang, Y. Jiang, and Y. Liu, “Variable Expanding Structure for Data Center Interconnection Networks,” J. Adv. Comput. Intell. Intell. Inform., Vol.25 No.1, pp. 13-22, 2021.
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