Adaptive Random Packet Sampling for Traffic Load Measurement 


Vol. 28,  No. 11, pp. 1038-1049, Nov.  2003


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  Abstract

Exactly measuring traffic load is the basis for efficient traffic engineering. However, precise traffic measurement involves inspecting every packet traversing a link. resulting in significant overhead on routers with high-speed links. Sampling techniques are proposed as an alternative way to reduce the measurement overhead. But, since sampling inevitably accompany with error, there should be a way to control, or at least limit, the error for traffic engineering applications to work correctly. In this paper, we address the problem of bounding sampling error within a pre-specified tolerance level. We derive a relationship between the number of samples, the accuracy of estimation and the squared coefficient of variation of packet size distribution. Based on this relationship, we propose an adaptive random sampling technique that determines the minimum sampling probability adaptively according to traffic dynamics. Using real network traffic traces, we show that the proposed adaptive random sampling technique indeed produces the desired accuracy, while also yielding significant reduction in the amount of traffic samples.

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  Cite this article

[IEEE Style]

J. Park, B. Choi, Z. Zhang, "Adaptive Random Packet Sampling for Traffic Load Measurement," The Journal of Korean Institute of Communications and Information Sciences, vol. 28, no. 11, pp. 1038-1049, 2003. DOI: .

[ACM Style]

Jaesung Park, Back-Young Choi, and Zhi-Li Zhang. 2003. Adaptive Random Packet Sampling for Traffic Load Measurement. The Journal of Korean Institute of Communications and Information Sciences, 28, 11, (2003), 1038-1049. DOI: .

[KICS Style]

Jaesung Park, Back-Young Choi, Zhi-Li Zhang, "Adaptive Random Packet Sampling for Traffic Load Measurement," The Journal of Korean Institute of Communications and Information Sciences, vol. 28, no. 11, pp. 1038-1049, 11. 2003.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880