BHyberCube: a MapReduce aware heterogeneous architecture for data center

Tao Jiang1, Huaxi Gu1, Kun Wang1, Xiaoshan Yu11 and Yunfeng Lu1

  1. State Key Laboratory of ISN, Xidian University
    Xi’an, China

Abstract

Some applications, like MapReduce, ask for heterogeneous network in data center network. However, the traditional network topologies, like fat tree and BCube, are homogeneous. MapReduce is a distributed data processing application. In this paper, we propose a BHyberCube network (BHC), which is a new heterogeneous network for MapReduce. Heterogeneous nodes and scalability issues are addressed considering the implementation of MapReduce in the existing topologies. Mathematical model is established to demonstrate the procedure of building a BHC. Comparisons of BHC and other topologies show the good properties BHC possesses for MapReduce. We also do simulations of BHC in multi-job injection and different probability of worker servers’ communications scenarios respectively. The result and analysis show that the BHC could be a viable interconnection topology in today’s data center for MapReduce.

Key words

Data center, MapReduce, topology

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS170202019T

Publication information

Volume 20, Issue 1 (January 2023)
Year of Publication: 2023
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

DownloadAvailable in PDF
Portable Document Format

How to cite

Jiang, T., Gu, H., Wang, K., Yu1, X., Lu, Y.: BHyberCube: a MapReduce aware heterogeneous architecture for data center. Computer Science and Information Systems, Vol. 20, No. 1, 611–627. (2023), https://doi.org/10.2298/CSIS170202019T