Open AccessBHyberCube: A MapReduce aware heterogeneous architecture for data center
Author(s) -
Tao Jiang,
Huaxi Gu,
Kun Wang,
Xiaoshan Yu,
Yunfeng Lu
Publication year - 2017
Publication title -
computer science and information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.244
H-Index - 24
eISSN - 2406-1018
pISSN - 1820-0214
DOI - 10.2298/csis170202019t
Subject(s) - computer science , network topology , scalability , heterogeneous network , distributed computing , server , data center , interconnection , homogeneous , network architecture , tree (set theory) , big data , computer network , database , data mining , telecommunications , wireless network , mathematical analysis , physics , mathematics , wireless , thermodynamics
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.
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