Data Center Network (DCN) research is gaining further momentum as the Cloud computing model proves scalable and efficient. As the economic efficiency of Cloud Computers improves with their size, Hyperclouds are now designed to contain 10,000 to 100,000 hosts. This extreme scale poses a challenge to DCN researchers, since building an experimental DCN of reasonable size is prohibitively expensive. Consequently, the research community greatly depends on the availability of formally defined traffic patterns, which describe the characteristics of Hyperscale DCN traffic. Even though several papers describing particular-cloud traffic were released over the years, no formal model was ever published or accepted as standard.

The DCTrafficGen package by Mellanox (https://www.mellanox.com/) provides a solution to this challenge by introducing a free to use, standard way of publishing traffic characteristics measured on hyperscale clusters. The package, is based on OMNeT++ event driven simulation technology that is free for academic use. DCTG generates traffic according to statistical profiles of flow duration, total size, packet size, message size, and destination locality. It also supports the definition of multiple application types in terms of the different roles of each Traffic Generator (TG) comprising the application, each with its own statistical or deterministic traffic injection characteristics. Then, it allows for describing the placement of multiple occurrences of these applications on specific network hosts. Each said host may contain a different number of TGs of each role representing the application occurrence.

The authors write: “DCTrafficGen is inspired by the detailed traffic characteristics provided in [1] and the simulator code of [2] that was generously made available to us. We hope our contribution will start a process of open source development and contributions of common traffic benchmarks, that will advance DCN research. We call for more groups to contribute application types, with new traffic statistics as well as code to improve our current implementation.”

[1] A. Roy, et al., “Inside the Social Network’s (Datacenter) Network,” in Proceedings of the 2015 SIGCOMM’15, pp. 123–137.

[2] B. Montazeri, et al., “Homa: A Receiver-Driven Low-Latency Transport Protocol Using Network Priorities,” in Proceedings of the 2018 SIGCOMM’18, pp. 221–235.