Accurate Recovery of Internet Traffic Data: A Sequential Tensor Completion Approach

doi:10.1109/TNET.2018.2797094

	Accurate Recovery of Internet Traffic Data: A Sequential Tensor Completion Approach
	Xie, Kun 1,2,3; Wang, Lele 1; Wang, Xin 3; Xie, Gaogang 4; Wen, Jigang 4; Zhang, Guangxing 4; Cao, Jiannong 5; Zhang, Dafang 1
	2018-04-01
发表期刊	IEEE-ACM TRANSACTIONS ON NETWORKING
ISSN	1063-6692
卷号	26 期号:2 页码:793-806
摘要	The inference of traffic volume of the whole network from partial traffic measurements becomes increasingly critical for various network engineering tasks, such as capacity planning and anomaly detection. Previous studies indicate that the matrix completion is a possible solution for this problem. However, as a 2-D matrix cannot sufficiently capture the spatial-temporal features of traffic data, these approaches fail to work when the data missing ratio is high. To fully exploit hidden spatial-temporal structures of the traffic data, this paper models the traffic data as a 3-way traffic tensor and formulates the traffic data recovery problem as a low-rank tensor completion problem. However, the high computation complexity incurred by the conventional tensor completion algorithms prevents its practical application for the traffic data recovery. To reduce the computation cost, we propose a novel sequential tensor completion algorithm, which can efficiently exploit the tensor decomposition result based on the previous traffic data to derive the tensor decomposition upon arriving of new data. Furthermore, to better capture the changes of data correlation over time, we propose a dynamic sequential tensor completion algorithm. To the best of our knowledge, we are the first to propose sequential tensor completion algorithms to significantly speed up the traffic data recovery process. This facilitates the modeling of Internet traffic with the tensor to well exploit the hidden structures of traffic data for more accurate missing data inference. We have done extensive simulations with the real traffic trace as the input. The simulation results demonstrate that our algorithms can achieve significantly better performance compared with the literature tensor and matrix completion algorithms even when the data missing ratio is high.
关键词	Internet traffic data recovery tensor completion
DOI	10.1109/TNET.2018.2797094
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61572184] ; National Natural Science Foundation of China[61725206] ; National Natural Science Foundation of China[61472130] ; National Natural Science Foundation of China[61472131] ; National Natural Science Foundation of China[61772191] ; Hunan Provincial Natural Science Foundation of China[2017JJ1010] ; Beijing Natural Science Foundation[4162057] ; Science and Technology Key Projects of Hunan Province[2015TP1004] ; U.S. ONR[N00014-17-1-2730] ; NSF[ECCS 1408247] ; NSF[CNS 1526843] ; NSF[ECCS 1731238] ; CAS Key Laboratory of Network Data Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences[CASNDST201704] ; China Academy of Sciences Equipment Project (Open Efficient Network Security Test System Development)
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000430596000011
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：74[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/5305
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Xie, Kun
作者单位	1.Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410006, Hunan, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, CAS Key Lab Network Data Sci & Technol, Beijing 100864, Peoples R China 3.SUNY Stony Brook, Dept Elect & Comp Engn, Stony Brook, NY 11794 USA 4.Chinese Acad Sci, Network Res Ctr, Inst Comp Technol, Beijing 100864, Peoples R China 5.Hong Kong Polytech Univ, Dept Comp, Hong Kong, Hong Kong, Peoples R China
推荐引用方式 GB/T 7714	Xie, Kun,Wang, Lele,Wang, Xin,et al. Accurate Recovery of Internet Traffic Data: A Sequential Tensor Completion Approach[J]. IEEE-ACM TRANSACTIONS ON NETWORKING,2018,26(2):793-806.
APA	Xie, Kun.,Wang, Lele.,Wang, Xin.,Xie, Gaogang.,Wen, Jigang.,...&Zhang, Dafang.(2018).Accurate Recovery of Internet Traffic Data: A Sequential Tensor Completion Approach.IEEE-ACM TRANSACTIONS ON NETWORKING,26(2),793-806.
MLA	Xie, Kun,et al."Accurate Recovery of Internet Traffic Data: A Sequential Tensor Completion Approach".IEEE-ACM TRANSACTIONS ON NETWORKING 26.2(2018):793-806.