T-product factorization method for internet traffic data completion with spatio-temporal regularization

Chen Ling (), Gaohang Yu (), Liqun Qi () and Yanwei Xu ()
Additional contact information
Chen Ling: Hangzhou Dianzi University
Gaohang Yu: Hangzhou Dianzi University
Liqun Qi: Huawei Theory Research Lab
Yanwei Xu: Huawei Theory Research Lab

Computational Optimization and Applications, 2021, vol. 80, issue 3, No 8, 883-913

Abstract: Abstract Recovery of network traffic data from incomplete observed data is an important issue in internet engineering and management. In this paper, by fully combining the temporal stability and periodicity features in internet traffic data, a new separable optimization model for internet data recovery is proposed, which is based upon the T-product factorization and the rapid discrete Fourier transform of tensors. The separable structural features presented in the model provide the possibility to design more efficient parallel algorithms. Moreover, by using generalized inverse matrices, an easy-to-operate and effective algorithm is proposed. In theory, we prove that under suitable conditions, every accumulation point of the sequence generated by the proposed algorithm is a stationary point of the established model. Numerical simulation results carried on the widely used real-world internet network datasets, show that the proposed method outperforms state-of-the-art competitions.

Keywords: Internet network traffic; Tensor completion; T-product factorization; Optimization method; Singular value decomposition; Block coordinate minimization algorithm (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10589-021-00315-1

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