We describe our experience building and deploying a demand-oblivious optically-switched network based on the RotorNet and Opera architectures. We detail the design, manufacture, deployment, and end-to-end operation of a 128-port optical rotor switch along with supporting NIC hardware and host software. Using this prototype, we assess yield, synchronization, and interoperability with commodity hardware and software at a scale of practical relevance. We provide the first real-world measurements of Linux TCP throughput and host-to-host latency in an operational RotorNet, achieving 98% of link rate with 99th-percentile ping times faster than commodity packet-switching hardware. In the process, we uncover unexpected challenges with link-level dropouts and devise a novel and flexible way to address them. Our deployment experience demonstrates the feasibility of our implementation approach and identifies opportunities for future exploration.

With the rise of heterogeneous congestion control algorithms and increasingly complex application control loops (e.g. adaptive bitrate algorithms), the Internet community has expressed growing concern that network bandwidth allocations are unfairly skewed, and that some Internet services are 'winners' at the expense of 'losing' services when competing over shared bottlenecks. In this paper, we provide the first study of fairness between live, end-to-end services with distinct workloads. Rather than focusing on individual components of an application stack (e.g., studying the fairness of an individual congestion control algorithm), we want to provide a direct study over real-world deployed applications. Among our findings, we observe that services typically achieve less-than-fair outcomes: on average, the 'losing' service achieves only 72% of its max-min fair share of link bandwidth. We also find that some services are significantly more contentious than others: for example, one popular file distribution service causes competing applications to obtain as low as 16% of their max-min fair share of bandwidth when competing in a moderately-constrained setting.

Much of our understanding of congestion control algorithm (CCA) throughput and fairness is derived from models and measurements that (implicitly) assume congestion occurs in the last mile. That is, these studies evaluated CCAs in "small scale" edge settings at the scale of tens of flows and up to a few hundred Mbps bandwidths. However, recent measurements show that congestion can also occur at the core of the Internet on inter-provider links, where thousands of flows share high bandwidth links. Hence, a natural question is: Does our understanding of CCA throughput and fairness continue to hold at the scale found in the core of the Internet, with 1000s of flows and Gbps bandwidths?