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The curriculum for a graduate Computer Networking course in Computer Science typically includes activities that help students gain a variety of practical skills that complement the theoretical knowledge they learn during the course. These skills are developed through exercises that present students with scenarios in which they are to understand or cause specific communication behavior over a network. These exercises are constrained by the computer resources that students use for learning. Ideally those resources can be tuned to increase the fidelity of the network that a student is managing—and ultimately allow each student to fully control their own network. This paper describes the motivation, process, and challenges of delivering a graduate course in networking using resources on FABRIC—a publicly-funded, international testbed for research in networking. The paper analyzes the experience of teaching three graduate courses on networking, and reflects on using FABRIC to (1) ensure that students have equal access to a high-quality network environment (rather than rely on students’ individual laptops or self-managed school equipment), and (2) exploit the research testbed’s flexibility to develop a rich range of exercises for students. We discuss our lessons learned and share advice for other instructors. 

Data Acquisition (DAQ) workloads form an important class of scientific network traffic that by its nature (1) flows across different research infrastructure, including remote instruments and supercomputer clusters, (2) has ever-increasing through-put demands, and (3) has ever-increasing integration demands—for example, observations at one instrument could trigger a reconfiguration of another instrument. Today’s DAQ transfers rely on UDP and (heavily tuned) TCP, but this is driven by convenience rather than suitability. The mismatch between Internet transport protocols and scientific workloads becomes more stark with the steady increase in link capacities, data generation, and integration across research infrastructure. This position paper argues the importance of developing specialized transport protocols for DAQ workloads. It proposes a new transport feature for this kind of elephant flow: multi-modality involves the network actively configuring the transport protocol to change how DAQ flows are processed across different underlying networks that connect scientific research infrastructure. Multi-modality is a layering violation that is proposed as a pragmatic technique for DAQ transport protocol design. It takes advantage of programmable network hardware that is increasingly being deployed in scientific research infrastructure. The paper presents an initial evaluation through a pilot study that includes a Tofino2 switch and Alveo FPGA cards, and using data from a particle detector. 

Packet filtering has remained a key network monitoring primitive over decades, even as networking has continuously evolved. In this article we present the results of a survey we ran to collect data from the networking community, including researchers and practitioners, about how packet filtering is used. In doing so, we identify pain points related to packet filtering, and unmet needs of survey participants. Based on analysis of this survey data, we propose future research and development goals that would support the networking community.