Multi-manifold model of the Internet delay space

Wang, Zhanfeng; Chen, Ming; Xing, Changyou; Feng, Jing; Wei, Xianglin; Bai, Huali

doi:10.1016/j.jnca.2012.09.003

Cited by 7 publications

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…IDES [10] is the first algorithm which based on this idea. But the multi manifold property of the Internet latency space [11] leads to ill-posed matrixes inversions computing inevitably, and then the accuracy of the latency estimation is dropped significantly. DMFSGD [12] algorithm imports a regularization factor to get a biased estimation of the latency through minimize the mean square error of the estimation error, which enhances the robustness substantially.…”

mentioning

confidence: 99%

NADeMaC: A simple non-negative decentralized completion algorithm for Internet latency matrix

2015

2015 IEEE International Conference on Progress in Informatics and Computing (PIC)

View full text Add to dashboard Cite

In this paper, the non-negative decentralized completion problem of the in-complete Internet latency matrix is studied. On the basis of the low-rank approximation of matrix, we componentize this problem into a couple of convex optimization problems by estimating the 10 norm of this matrix, and then solve it by alternative direction algorithm. Owing to the asymmetry and the negative definite characteristic of the matrix caused by the difference between autonomous system routing strategies, some negative entries inevitably exist in the completed matrix. Unlike traditional non-negative completion algorithms, this paper does not try to prevent the generation of negative entries. As an alternative, this paper presents a novel and much simpler non-negative ensuring scheme named NADeMaC, which calibrates the negative entries by a prior positive estimation value after they appeare. Theoretical analysis shows that the accuracy of our algorithm is at least no less than traditional methods. Furthermore, our experiments show that our method is far better than traditional non-negative ensuring scheme.

show abstract

mentioning

confidence: 99%