Measurement of One-Way Transit Time in IP Routers Adrian Popescu and Doru Constantinescu Dept. of Telecommunication Systems School of Engineering Blekinge Institute of Technology 371 79 Karlskrona, Sweden Abstract The main goals of the tutorial are towards an understanding of the delay process in best-effort Internet for both non-congested and congested networks. A novel measurement system is reported for delay measurements in IP routers, which follows specifications of the IETF RFC 2679. The system is using both passive measurements and active probing and offers the possibility to measure and analyze different delay components of a router, e.g., packet processing delay, packet transmis- sion time and queueing delay at the output link. Dedicated application-layer software is used to generate UDP traffic with TCP-like characteristics. Pareto traffic models are used to generate self- similar traffic in the link. The reported results are in form of several important statistics regarding processing and queueing delays of a router, router delay for a single data flow, router delay for more data flows as well as end-to-end delay for a chain of routers. We confirm results reported earlier about the fact that the delay in IP routers is generally influenced by traffic characteristics, link conditions and, at some extent, details in hardware implementation and different IOS releases. The delay in IP routers may also occasionally show extreme values, which are due to improper functioning of the routers. Furthermore, new results have been obtained that indicate that the delay in IP routers shows heavy-tailed characteristics, which can be well modeled with the help of three distributions, either in the form of single distribution or as a mixture of two distributions. There are several components contributing to the One-Way Transit Time (OWTT) in routers, i.e., processing delay, queueing delay and service time. Our results have shown that, e.g., the processing delay in a router can be modeled with the Normal or skewed Normal distribution, and the queueing delay is well modeled with a mixture of Normal distribution for the body probability mass and of Weibull distribution for the tail probability mass. It has been also observed that One-Way Transit Time (OWTT) is well modeled with the generalized Pareto distribution. Furthermore, OWTT has several component delays and it has been observed that the component delay distribution that is most dominant and heavy-tailed has a decisive influence on OWTT. To the best of our knowledge, this is the first time we understand the distributional properties of the delay process in an IP router. Keywords: traffic measurements, traffic modeling, IP routers, one-way transit time, traffic capturing software, traffic self-similarity 1 Introduction As the Internet emerges as the backbone of worldwide business and commercial activities, end-to-end (e2e) Quality of Service (QoS) for data transfer becomes a significant factor. End-to-end delay is a key metric in evaluating the performance of networks as well as the quality of service perceived by end users. Today network capacities are being deliberately overengineered in the Internet so that the packet loss rate is very low. Throughput maximization can be done by minimizing the e2e delay. However, given the heterogeneity of the network and the fact that the overengineering 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 [27, 29]. Several papers report on e2e delay performance, and both Round-Trip Time (RTT) and One-Way Transit Time (OWTT) are considered [5, 8, 29, 31]. Traffic measurements based on both passive mea- 1/38