Networking research has long relied on simulation as the primary vehicle for demonstrating the effectiveness of proposed protocols and mechanisms. Typically, one simulates network hardware and software in software using, for example, the widely used ns-2 simulator. Experimentation proceeds by simulating the use of the network by a given population of users using applications such as ftp or web browsers. Synthetic workload generators are used to inject data into the network according to a model of how the applications or users behave.
In order to perform realistic network simulations, one needs a traffic generator that is capable of generating realistic synthetic traffic in a closed-loop fashion that ?looks like? traffic found on an actual network. Unfortunately, the networking community suffers from a lack of validated tools and models suitable for synthetic traffic generation. As a result, all too often, networking technology is evaluated using ad hoc workloads with an unknown relationship to traffic seen on real links and hence begs the question of how believable the results of the evaluation are.
This project is a collaborative effort to develop a synthetic traffic generation resource for the experimental networking research community. The resource consists of (1) synthetic traffic generators for the ns-2, ns-3, and GTNets software simulators, and Linux and BSD-based testbeds, (2) a repository of datasets to be used by the traffic generators to generate traffic that is statistically equivalent to traffic found on a variety of network links including campus networks, wide-area backbone networks, corporate intranets, wireless networks, etc, and (3) a set of traffic analysis tools to enable researchers to generate empirical models of traffic on network links of interest and to use these models to drive the synthetic traffic generation process.
