On Creating Proportional Loss-Rate Differentiation: Predictability and Performance

— 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 loss-rate (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.

• Type: Conference
• Year: 2001
• Where: IWQOS
• Authors: Ulf Bodin, Andreas Jonsson, Olov Schelén
• Keywords: ADD Estimator, Communications, Drop Precedence, IWQOS 2001, Loss-rate Ratios