Does a building have a spirit? Does an innovative building design make certain kinds of creativity and collaborations possible that could not be realized in a traditional structure? Are the ways that humans have used a building in the past — their accomplishments, experiences, and artworks — an inherent part of that building’s legacy? How can we use virtual reality to preserve a structure (and its spirit, or its archival legacy) that is otherwise abandoned and off-limits?

Defining a universal metric for Quality of Experience (QoE) is notoriously hard due to the complex relationship between low-level performance metrics and user satisfaction. The most common metric, the Mean Opinion Score (MOS), has well-known biases and inconsistency issues. We propose an alternative that leverages (a) social-media comments on network performance and (b) streaming footage that includes performance numbers. We argue that our proposal is feasible for online gaming, and it may apply to other applications in the near future. We discuss its potential to enable a direct mapping from low-level performance metrics to accurate QoE scores---the golden standard for assessing user satisfaction.

Keeping track of Internet latency is a classic measurement problem. Open measurement platforms like RIPE Atlas are a great solution, but they also face challenges: preventing network overload that may result from uncontrolled active measurements, and maintaining the involved devices, which are typically contributed by volunteers and non-profit organizations, and tend to lag behind the state of the art in terms of features and performance. We explore gaming footage as a new source of real-time, publicly available, passive latency measurements, which have the potential to complement open measurement platforms. We show that it is feasible to mine this source of information by presenting Tero, a system that continuously downloads gaming footage from the Twitch streaming platform, extracts latency measurements from it, and converts them to latency distributions per geographical location. Our data-sets and source code are publicly available at https://nal-epfl.github.io/tero-project.

Data processing and distributed querying workloads often involve a "scatter-gather" or "partition-aggregate" architectural pattern, whereby one application queries hundreds or even thousands of workers. Network communication is often a bottleneck in this pattern, especially when the compute task at each worker is small, such as for Web queries and interactive analytics. The network bottleneck can result in low throughput, high CPU utilization, and cause job completion time to increase by orders of magnitude. To overcome these inefficiencies, we explore hardware-offload of the scatter-gather primitive, whereby a smart NIC takes on the responsibility of sending out queries and collecting responses. We show that this approach not only virtually eliminates CPU usage, but with suitable scheduling of responses, it also speeds up scatter by allowing parallel queries, and gather by preventing throughput collapse due to excessive congestion. Besides response scheduling, we use a careful design at the NIC to limit FPGA resource usage: our approach uses about 25% of on-chip logic and 33% of on-chip memory on a mid-sized FPGA, leaving enough room for implementing other functions on the smart NIC.