Queuing Performance of Long-Range Dependent Traffic Regulated by Token-Bucket Policers

Long-range dependence (LRD) is a widely verified property of Internet traffic, which severeiy affects network performance yielding longer queuing delays. Token-bucket policers are commonly proposed to enforce the statistical profile of input traffic, but they can hardly reduce LRD and thus can be ineffective to protect service level agreements against LRD increase in input traffic. In this paper, we investigate by simulation the queuing performance in a downstream scheduler of LRD traffic regulated by token-bucket policers. We compare the delay distributions of regulated and unregulated LRD flows. We demonstrate that policers reduce significantly the downstream queuing delay, although they do not alter much the 1/falpha spectrum of regulated traffic. We observe also that the policed traffic does not obey a plain fractional Gaussian traffic model: first, it is not Gaussian anymore; moreover, also its third-order two-lags covariance is altered by the policer. Finally, we point out that policers can reduce noticeably the negative impact of traffic LRD increase on queuing delay, although they can diminish actual LRD only slightly.