CLC number: TP306
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2021-05-07
Cited: 0
Clicked: 6158
Citations: Bibtex RefMan EndNote GB/T7714
Yining Qi, Chongrong Fang, Haoyu Liu, Daxiang Kang, Biao Lyu, Peng Cheng, Jiming Chen. A survey of cloud network fault diagnostic systems and tools[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(8): 1031-1045.
@article{title="A survey of cloud network fault diagnostic systems and tools",
author="Yining Qi, Chongrong Fang, Haoyu Liu, Daxiang Kang, Biao Lyu, Peng Cheng, Jiming Chen",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="22",
number="8",
pages="1031-1045",
year="2021",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000153"
}
%0 Journal Article
%T A survey of cloud network fault diagnostic systems and tools
%A Yining Qi
%A Chongrong Fang
%A Haoyu Liu
%A Daxiang Kang
%A Biao Lyu
%A Peng Cheng
%A Jiming Chen
%J Frontiers of Information Technology & Electronic Engineering
%V 22
%N 8
%P 1031-1045
%@ 2095-9184
%D 2021
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000153
TY - JOUR
T1 - A survey of cloud network fault diagnostic systems and tools
A1 - Yining Qi
A1 - Chongrong Fang
A1 - Haoyu Liu
A1 - Daxiang Kang
A1 - Biao Lyu
A1 - Peng Cheng
A1 - Jiming Chen
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 22
IS - 8
SP - 1031
EP - 1045
%@ 2095-9184
Y1 - 2021
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2000153
Abstract: Recently, cloud computing has become a vital part that supports people’s normal lives and production. However, accompanied by the increasing complexity of the cloud network, failures constantly keep coming up and cause huge economic losses. Thus, to guarantee the cloud network performance and prevent execrable effects caused by failures, cloud network diagnostics has become of great interest for cloud service providers. Due to the characteristics of cloud network (e.g., virtualization and multi-tenancy), transplanting traditional network diagnostic tools to the cloud network face several difficulties. Additionally, many existing tools cannot solve problems in the cloud network. In this paper, we summarize and classify the state-of-the-art technologies of cloud diagnostics which can be used in the production cloud network according to their features. Moreover, we analyze the differences between cloud network diagnostics and traditional network diagnostics based on the characteristics of the cloud network. Considering the operation requirements of the cloud network, we propose the points that should be cared about when designing a cloud network diagnostic tool. Also, we discuss the challenges that cloud network diagnostics will face in future development.
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