Paper Info
Title
A Failure-Tolerant and Spectrum-Efficient Wireless Data Center Network Design for Improving Performance of Big Data Mining
Abstract
Wireless Data Center Network (Wi-DCN) is considered one of the most promising future data center architectures due to its low installation and management cost and high flexibility of network design. However, the existing Wi-DCN is, still, not capable of providing an efficient big data mining service such as MapReduce because its topology (i.e., Cayley graph with same degree) cannot achieve enough connectivity on the breakdown of servers and spectrum efficiency, which are important factors to improve the performance of big data mining. Therefore, in order to modify the existing Wi-DCN for big data mining, this paper proposes a spherical rack architecture based on a bimodal degree distribution that improves both failure tolerance and spectrum efficiency. Extensive computer simulations demonstrate the effectiveness of our proposed rack architecture in terms of data transmission time required for MapReduce under a failure-prone environment.
Year
DOI
Venue
2015
10.1109/VTCSpring.2015.7145601
2015 IEEE 81st Vehicular Technology Conference (VTC Spring)
Keywords
Field
DocType
spectrum-efficient wireless data center network design,failure-tolerant wireless data center network design,Big Data mining service,Wi-DCN,data center architectures,management cost,MapReduce,spherical rack architecture,bimodal degree distribution,computer simulations,data transmission time
Architecture,Rack,Network planning and design,Computer science,Cayley graph,Server,Computer network,Degree distribution,Spectral efficiency,Data center
Conference
ISSN
Citations 
PageRank 
1550-2252
4
0.45
References 
Authors
8
6
Name
Order
Citations
PageRank
Katsuya Suto112211.03
Hiroki Nishiyama2128592.61
Nei Kato33982263.66
takayuki nakachi45216.65
Toshikazu Sakano510310.97
takahara613218.65