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MD-AVB: A Multi-Manifold Based Available Bandwidth Prediction Algorithm

Institute of Network Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Institute for Network Sciences and Cyberspace, Tsinghua University, Beijing 100084, China.
School of Computer Science and Engineering, Southeast University, Nanjing 211189, China.
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Abstract

The performance of Internet applications is heavily affected by the end-to-end available bandwidth. Thus, it is very important to examine how to accurately predict the available Internet bandwidth. A number of available bandwidth prediction algorithms have been proposed to date, but none of the existing solutions are able to achieve a high level of accuracy. In this paper, a Multi-manifold based Available Bandwidth prediction algorithm (MD-AVB) is proposed, based on the observation that the available bandwidth space on the Internet is multi-manifold and asymmetrical. In the proposed algorithm, the available bandwidth space is divided into multiple lower-dimensional domains iteratively, and each domain is embedded separately to predict the available bandwidth. Experiments on HP S3 datasets demonstrate that the proposed algorithm is more accurate than existing approaches.

References

[1]
N. N. Hu and P. Steenkiste, Exploiting internet route sharing for large scale available bandwidth estimation, in Proc. 5th ACM SIGCOMM Conf. Internet Measurement, Berkeley, CA, USA, 2005, p. 16.
[2]
A. Shriram, Efficient techniques for end-to-end bandwidth estimation: Performance evaluations and scalable deployment, https://cdr.lib.unc.edu/concern/dissertations/vm40xs86h, 2009.
[3]
C. Y. Xing, M. Chen, and L. Yang, Predicting available bandwidth of internet path with ultra metric space-based approaches, in Proc. GLOBECOM 2009—2009 IEEE Global Telecommunications Conf., Honolulu, HI, USA, 2009.
[4]
P. Key, L. Massoulié, and D. C. Tomozei, Non-metric coordinates for predicting network proximity, in Proc. IEEE INFOCOM 2008—The 27th Conf. on Computer Communications, Phoenix, AZ, USA, 2008, pp. 1840-1848.
[5]
T. S. E. Ng and H. Zhang, Predicting internet network distance with coordinates-based approaches, in Proc. 21st Ann. Joint Conf. of the IEEE Computer and Communications Societies, New York, NY, USA, 2002.
[6]
F. Dabek, R. Cox, F. Kaashoek, and R. Morris, Vivaldi: A decentralized network coordinate system, ACM SIGCOMM Comp. Commun. Rev., vol. 34, no. 4, pp. 15-26, 2004.
[7]
V. Ramasubramanian, D. Malkhi, F. Kuhn, M. Balakrishnan, A. Gupta, and A. Akella, On the treeness of internet latency and bandwidth, in Proc. 11th Int. Joint Conf. on Measurement and Modeling of Computer Systems, Seattle, WA, USA, 2009.
[8]
S. Song, P. J. Keleher, and A. Sussman, Searching for bandwidth-constrained clusters, in Proc. 31st Int. Conf. on Distributed Computing Systems, Minneapolis, MN, USA, 2011.
[9]
C. Y. Xing, G. M. Zhang, B. Xu, C. Hu, and M. Chen, A hierarchical internet path available bandwidth inference mechanism, J. Int. Technol., vol. 18, no. 1, pp. 135-146, 2017.
[10]
P. Yalagandula, P. Sharma, S. Banerjee, S. Basu, and S. Lee, S3: A scalable sensing service for monitoring large networked systems, in Proc. of 2006 SIGCOMM Workshop on Internet network Management, Pisa, Italy, 2006.
[11]
Y. Wang, Y. Jiang, Y. Wu, and Z. H. Zhou, Multi-manifold clustering, in Proc. 11th Pacific Rim Int. Conf. on Trends in Artificial Intelligence, Daegu, Korea, 2010.
[12]
I. T. Jolliffe, Principal Component Analysis. Springer, 2011.
[13]
J. B. Tenenbaum, V. De Silva, and J. C. Langford, A global geometric framework for nonlinear dimensionality reduction, Science, vol. 290, no. 5500, pp. 2319-2323, 2000.
[14]
A. Ghodsi, Dimensionality reduction a short tutorial, https://www.math.uwaterloo.ca/~aghodsib/courses/f06stat890/readings/tutorial_stat890.pdf, 2006.
[15]
Z. F. Wang, M. Chen, C. Y. Xing, and G. M. Zhang, T-aware: An AS topology based available bandwidth prediction algorithm, (in Chinese), J. Beijing Univ. Posts Telecommun., vol. 34, no. 3, pp. 66-70, 2011.
Tsinghua Science and Technology
Pages 140-148
Cite this article:
Zhang P, An C, Wang Z, et al. MD-AVB: A Multi-Manifold Based Available Bandwidth Prediction Algorithm. Tsinghua Science and Technology, 2020, 25(1): 140-148. https://doi.org/10.26599/TST.2019.9010002
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