Measurement and analysis of single-hop delay on an IP backbone network

Abstract

Abstract-We measure and analyze the single-hop packet delay through operational routers in the Sprint Internet protocol (IP) backbone network. After presenting our delay measurements through a single router for OC-3 and OC-12 link speeds, we propose a methodology to identify the factors contributing to single-hop delay. In addition to packet processing, transmission, and queueing delay at the output link, we observe the presence of very large delays that cannot be explained within the context of a first-in first-out output queue model. We isolate and analyze these outliers.Results indicate that there is very little queueing taking place in Sprint's backbone. As link speeds increase, transmission delay decreases and the dominant part of single-hop delay is packet processing time. We show that if a packet is received and transmitted on the same linecard, it experiences less than 20 s of delay. If the packet is transmitted across the switch fabric, its delay doubles in magnitude. We observe that processing due to IP options results in single-hop delays in the order of milliseconds. Milliseconds of delay may also be experienced by packets that do not carry IP options. We attribute those delays to router idiosyncratic behavior that affects less than 1% of the packets. Finally, we show that the queueing delay distribution is long-tailed and can be approximated with a Weibull distribution with the scale parameter = 0 5 and the shape parameter = 0 6 to 0.82. Index Terms-Link utilization, queueing delay, single-hop delay measurement.

On Kleinrock’s Independence Assumption

“…They also seem to be correlated with packet loss rates [19]. Periodic delay spikes and packet losses have been observed, which seem to be a consequence of routing flaps [18].…”

“…Today, the situation is such as it is not clear what the arrival processes at downstream queues are, and therefore it is impossible to do a precise analysis like, e.g., in the case of M/M/1 or M/G/1 queueing systems. Delay models based on Poisson assumptions are totally inappropriate for analysis at downstream queues and no analytical solutions are actually known for even a simple tandem queueing system with Poisson arrivals and Exponentially distributed service times [2,4,18].…”

“…However, given the heterogeneity of the network and the fact that the overprovisioning solution is not adopted everywhere, especially not by backbone teleoperators in developing countries, the question arises as to how the delay performance impacts the e2e performance. There are several important parameters that may impact the e2e delay performance in the link, e.g., traffic self-similarity, routing flaps and link utilization [16,18].…”

“…Several publications report on the e2e delay performance, and both Round-Trip Time (RTT) and One-Way Transit Time (OWTT) are considered [4,6,18,19].…”

“…The heavy tail behavior is due to the presence of self-similarity in Internet packet delay [3]. Typical queueing models like M/M/1, M/G/1 and using Fractional Brownian Models (fBm) for traffic models have been shown to underestimate average queueing delays for link utilization below 70% [18]. Furthermore, another important question is regarding the impact on OWTT performance of diverse correlations existent in a tandem queueing system and whether Kleinrock's independence assumption [14] is valid.…”