Abstract
Recent extensions to the Internet architecture allow assignment of different levels of drop precedence to IP packets. This paper examines differentiation predictability and implementation complexity in creation of proportional lossrate (PLR) differentiation between drop precedence levels. PLR differentiation means that fixed loss-rate ratios between different traffic aggregates are provided independent of traffic loads. To provide such differentiation, running estimates of loss-rates can be used as feedback to keep loss-rate ratios fixed at varying traffic loads. In this paper, we define a loss-rate estimator based on average drop distances (ADDs). The ADD estimator is compared with an estimator that uses a loss history table (LHT) to calculate loss-rates. We show, through simulations, that the ADD estimator gives more predictable PLR differentiation than the LHT estimator. In addition, we show that a PLR dropper using the ADD estimator can be implemented efficiently.
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© 2001 Springer-Verlag Berlin Heidelberg
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Bodin, U., Jonsson, A., Schelén, O. (2001). On Creating Proportional Loss-Rate Differentiation: Predictability and Performance. In: Wolf, L., Hutchison, D., Steinmetz, R. (eds) Quality of Service — IWQoS 2001. IWQoS 2001. Lecture Notes in Computer Science, vol 2092. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45512-4_29
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DOI: https://doi.org/10.1007/3-540-45512-4_29
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