Anomaly Detection for Nodes Under the Cloud Computing Environment

被引:0
作者
Lei, Yang [1 ]
Jiang, Ying [1 ]
机构
[1] Kunming Univ Sci & Technol, Kunming, Yunnan, Peoples R China
基金
中国国家自然科学基金;
关键词
Anomaly Detection; Cloud Computing Environment; Directly Associated Node; Indirectly Associated Node; Single Node;
D O I
10.4018/IJDST.2021010103
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Due to the services diversity and dynamic deployment, the anomalies will occur on nodes under cloud computing environment. If a single node generates an anomaly, the associated nodes are affected by the abnormal node, which will result in anomaly propagation and nodes failure. In this paper, a method of anomaly detection for nodes under the cloud computing environment is proposed. Firstly, the node monitoring model is established by the agents deployed on each node. Secondly, the comprehensive score is used to identify abnormal data. The anomaly of the single node is judged by the time windowbased method. Then, the status of directly associated nodes is detected through normalized mutual information and the status of indirectly associated nodes is detected through the node attributes in the case of a single node anomaly. Finally, other associated nodes affected by the abnormal node are detected. The experimental results showed that the method in this paper can detect the anomalies of single node and associated node under the cloud computing environment effectively.
引用
收藏
页码:30 / 48
页数:19
相关论文
共 26 条
[1]   A View of Cloud Computing [J].
Armbrust, Michael ;
Fox, Armando ;
Griffith, Rean ;
Joseph, Anthony D. ;
Katz, Randy ;
Konwinski, Andy ;
Lee, Gunho ;
Patterson, David ;
Rabkin, Ariel ;
Stoica, Ion ;
Zaharia, Matei .
COMMUNICATIONS OF THE ACM, 2010, 53 (04) :50-58
[2]  
Chen Q., 2016, 2016 12 INT C COMP I
[3]  
FU S, 2011, P IEEE GLOB COMM C G
[4]  
Guan Q., 2013, 2013 IEEE 32 INT S R
[5]   RPR: recommendation for passengers by roads based on cloud computing and taxis traces data [J].
Jing, Weipeng ;
Hu, Likun ;
Shu, Lei ;
Mukherjee, Mithun ;
Hara, Takahiro .
PERSONAL AND UBIQUITOUS COMPUTING, 2016, 20 (03) :337-347
[6]  
Kang H., 2010, P 7 INT C AUTONOMIC, P119
[7]   Toward Automated Anomaly Identification in Large-Scale Systems [J].
Lan, Zhiling ;
Zheng, Ziming ;
Li, Yawei .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2010, 21 (02) :174-187
[8]   A Failure Detection System for Large Scale Distributed Systems [J].
Lavinia, Andrei ;
Dobre, Ciprian ;
Pop, Florin ;
Cristea, Valentin .
INTERNATIONAL JOURNAL OF DISTRIBUTED SYSTEMS AND TECHNOLOGIES, 2011, 2 (03) :64-87
[9]  
Lei Y., 2020, COMPUTER SCI
[10]  
Lei Y., 2019, 2019 IEEE INT C COMP, DOI [10.1109/CSEI47661.2019.8938912, DOI 10.1109/CSEI47661.2019.8938912]