Invited Lecture: Theophilus Benson

Demystifying and controlling the performance of data center networks

Although there is tremendous interest in designing improved networks for data centers, very little is known about the network-level traffic characteristics of current data centers. In this talk, I will present an empirical study of the network traffic in 10 data centers and show how observations from this study can be used to design more efficient traffic engineering techniques for current data centers. First, I will describe the flow-level and packet-level transmission properties of the applications within these data centers, and their impact on network utilization, link utilization, congestion, and packet drops. I will briefly discuss the implications of the observed traffic patterns for data center internal traffic engineering as well as for recently-proposed architectures for data center networks. Next, I will present an overview of MicroTE, a system that adapts to traffic variations by leveraging the short term and partial predictability of the traffic matrix. I will show that MicroTE performs close to the optimal solution and imposes minimal overhead on the network making it appropriate for current and future data centers. Finally, I will conclude by discussing the implications of my techniques and observations on application performance. Towards that end, I will also give a brief overview of ongoing work to provide better visibility into application performance.

Biography

Theophilus Benson is passionate about improving the reliability, availability and performance of networks both within local area networks and within the cloud. His work has focused on configuration management, data center networks, and cloud computing. This work has earned him IBM fellowships, a best paper award at IMC 2010, and, more recently, his cloud computing platform was acquired by a large cloud provider. He will be joining Duke University as an Assistant Professor in July 2013. Currently, he is doing a Post-Doc at Princeton University with Jennifer Rexford. Prior to that, he received his Ph.D. and M.S. in Computer Science at the University of Wisconsin and worked as a software engineer at an MIT based startup in Waltham, MA.