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High-Efficiency Remote Cloud Data Center Backup
with Intelligent Parameter Adaptation
Bao Rong Chang 1,∗ , Hsiu-Fen Tsai 2 , Cin-Long Guo 1 , Chia-Yen Chen 1 ,
and Chien-Feng Huang 1
1 Department of Computer Science and Information Engineering, National University of
Kaohsiung 81148, Taiwan
{brchang,m1015504,ayen,cfhuang15}@nuk.edu.tw
2 Department of Marketing Management, Shu Te University, Kaohsiung 82445, Taiwan
soenfen@stu.edu.tw
Abstract. This paper aims to realize high efficient remote cloud data center
backup using HBase and Cassandra, and in order to verify the high efficiency
backup they have applied Thrift Java for cloud data center to take a stress test
by performing strictly data read/write and remote backup in the large amounts
of data. In order to optimize traffic flow of data center backup, adaptive
network-based fuzzy inference system (ANFIS) along with particle swarm
optimization (PSO) has been employed to off-line tune seamless handoff and
network traffic flow. Finally, in terms of the effectiveness-cost evaluation to
assess the remote database backup, a cost-performance ratio has been evaluated
for several benchmark databases and the proposed ones. As a result, the
proposed HBase approach outperforms the other databases.
Keywords: NoSQL Database, HBase, Cassandra, Remote Data Center,
Backup, ANFIS-PSO, Thrift Java.
1
Introduction
In recent years, cloud services [1][2] are applicable in our daily lives. Many
traditional services such as telemarketing, television and advertisement are evolving
into digitized formats. As smart devices are gaining popularity and usage, the
exchange of information is no longer limited to just desktop computers, but instead,
information is transferred through portable smart devices [3][4], so that humans can
receive prompt and up-to-date information anytime. This leads to the emergence of
non-relational databases, of which many notable NoSQL databases that are currently
being used by enterprises are HBase [5], Cassandra [6], and Mongo [7].
This paper will implement data center remote backup using two remarkable
NoSQL databases HBase and Cassandra, and perform stress tests with a large scale of
data, for instances, read, write, and remote data center backup. Furthermore, in order
to maintain data center backup over internet smoothly, we proposed an intelligent
Corresponding author.
 
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