Data centers must support a range of workloads with differing demands. Although existing approaches handle routine traffic smoothly, intense hotspots--even if ephemeral--cause excessive packet loss and severely degrade performance. This loss occurs even though congestion is typically highly localized, with spare buffer capacity at nearby switches. In this paper, we argue that switches should share buffer capacity to effectively handle this spot congestion without the monetary hit of deploying large buffers at individual switches. Specifically, we present detour-induced buffer sharing (DIBS), a mechanism that achieves a near lossless network without requiring additional buffers at individual switches. Using DIBS, a congested switch detours packets randomly to neighboring switches to avoid dropping the packets. We implement DIBS in hardware, on software routers in a testbed, and in simulation, and we demonstrate that it reduces the 99th percentile of delay-sensitive query completion time by up to 85%, with very little impact on other traffic.

Internet routing suffers from persistent and transient failures, circuitous routes, oscillations, and prefix hijacks. A major impediment to progress is the lack of ways to conduct impactful interdomain research. Most research is based either on passive observation of existing routes, keeping researchers from assessing how the Internet will respond to route or policy changes; or simulations, which are restricted by limitations in our understanding of topology and policy.

Software bugs are inevitable in software-defined networking control software, and troubleshooting is a tedious, time-consuming task. In this paper we discuss how to improve control software troubleshooting by presenting a technique for automatically identifying a minimal sequence of inputs responsible for triggering a given bug, without making assumptions about the language or instrumentation of the software under test. We apply our technique to five open source SDN control platforms---Floodlight, NOX, POX, Pyretic, ONOS---and illustrate how the minimal causal sequences our system found aided the troubleshooting process.

Today's data centers must support a range of workloads with different demands. While existing approaches handle routine traffic smoothly, ephemeral but intense hotspots cause excessive packet loss and severely degrade performance. This loss occurs even though the congestion is typically highly localized, with spare buffer capacity available at nearby switches.

In this demo, we present Ripcord, a modular platform for rapidly prototyping scale-out data center networks. Ripcord enables researchers to build and evaluate new network features and topologies, using only commercially available hardware and open-source software. The Ripcord demo will show three examples of custom network functions, operating together, on top of a 160-node cluster. The first is a routing engine that isolates classes of traffic. The second is a dynamic network manager than adjusts links and switch power states to reduce energy. The third is a statistics aggregator that supports network health monitoring and automatic alerts. The demo will be interactive, with a visualization of live parameters for each link and switch, such as bandwidth, drops, and power status, as well a control panel to modify the traffic load. We feel that an interactive demo is the best way to introduce the research community to Ripcord and get their feedback.