Abstract
TCP understands all packet losses as buffer overflows and reacts to such congestions by reducing its rate. In hybrid wired/wireless networks where a non negligible number of packet losses are due to link errors, TCP is unable to sustain a reasonable rate. In this paper, we propose to extend TCP Newreno with a packet loss classifier built by a supervised learning algorithm called ’decision tree boosting’. The learning set of the classifier is a database of 25,000 packet loss events in a thousand of random topologies. Since a limited percentage of wrong classifications of congestions as link errors is allowed to preserve TCP-Friendliness, our protocol computes this constraint dynamically and tunes a parameter of the classifier accordingly to maximise the TCP rate. Our classifier outperforms the Veno and Westwood classifiers by achieving a higher rate in wireless networks while remaining TCP-Friendly.
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El Khayat, I., Geurts, P., Leduc, G. (2005). Improving TCP in Wireless Networks with an Adaptive Machine-Learnt Classifier of Packet Loss Causes. In: Boutaba, R., Almeroth, K., Puigjaner, R., Shen, S., Black, J.P. (eds) NETWORKING 2005. Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications Systems. NETWORKING 2005. Lecture Notes in Computer Science, vol 3462. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11422778_44
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DOI: https://doi.org/10.1007/11422778_44
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