A machine learning-based approach for estimating available bandwidth

Ling Jyh Chen, Cheng Fu Chou, Bo Chun Wang

研究成果: 書貢獻/報告類型會議貢獻

4 引文 斯高帕斯(Scopus)

摘要

In this paper, we propose a machine learning-based approach for estimating available bandwidth. We evaluate the approach via simulations using two probing models: a packet train probing model and a pathChirp-like probing model. The simulation results show that the former cannot yield accurate estimates in our system; however, using the pathChirp-like probing model, the proposed approach can estimate the available bandwidth with moderate traffic overhead more accurately than two widely used tools, pathChirp and Spruce. Moreover, we propose a normalization method that improves our approach's ability to estimate available bandwidth, even if there are no samples with similar properties to the measured path in the training dataset. The effectiveness and simplicity of this novel approach make it a promising scheme that goes a long way toward achieving accurate estimation of available bandwidth on Internet paths.

原文英語
主出版物標題TENCON 2007 - 2007 IEEE Region 10 Conference
DOIs
出版狀態已發佈 - 2007 十二月 1
事件IEEE Region 10 Conference, TENCON 2007 - Taipei, 臺灣
持續時間: 2007 十月 302007 十一月 2

出版系列

名字IEEE Region 10 Annual International Conference, Proceedings/TENCON

其他

其他IEEE Region 10 Conference, TENCON 2007
國家臺灣
城市Taipei
期間07/10/3007/11/2

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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    Chen, L. J., Chou, C. F., & Wang, B. C. (2007). A machine learning-based approach for estimating available bandwidth. 於 TENCON 2007 - 2007 IEEE Region 10 Conference [4428812] (IEEE Region 10 Annual International Conference, Proceedings/TENCON). https://doi.org/10.1109/TENCON.2007.4428812