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Today's networks are maintained by "masters of complexity": network admins who have accumulated the wisdom to troubleshoot complex problems, despite a limiting toolset. This position paper advocates a more structured troubleshooting approach that leverages architectural layering in SoftwareDefined Networks (SDNs). In all networks, high-level intent (policy) must correctly map to low-level forwarding behavior (hardware configuration). In SDNs, intent is explicitly expressed, forwarding semantics are explicitly defined, and each architectural layer fully specifies the behavior of the network. Building on these observations, we show how recently-developed troubleshooting tools fit into a coherent workflow that detects mistranslations between layers to precisely localize sources of errant control logic. Our goals are to explain the overall picture, show how the pieces fit together to enable a systematic workflow, and highlight the questions that remain. Once this workflow is realized, network admins can formally verify that their network is operating correctly, automatically troubleshoot bugs, and systematically track down their root cause -freeing admins to fix problems, rather than diagnose their symptoms.

Software bugs are inevitable in software-defined networking control software, and troubleshooting is a tedious, time-consuming task. In this thesis 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. AcknowledgmentsMany thanks to the STS team for making this thesis possible:

Software bugs are inevitable in software-defined networking control software, and troubleshooting is a tedious, time-consuming task. In this thesis 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. AcknowledgmentsMany thanks to the STS team for making this thesis possible:

Modern enterprises almost ubiquitously deploy middlebox processing services to improve security and performance in their networks. Despite this, we find that today's middlebox infrastructure is expensive, complex to manage, and creates new failure modes for the networks that use them. Given the promise of cloud computing to decrease costs, ease management, and provide elasticity and faulttolerance, we argue that middlebox processing can benefit from outsourcing the cloud. Arriving at a feasible implementation, however, is challenging due to the need to achieve functional equivalence with traditional middlebox deployments without sacrificing performance or increasing network complexity.In this paper, we motivate, design, and implement APLOMB, a practical service for outsourcing enterprise middlebox processing to the cloud. Our discussion of APLOMB is data-driven, guided by a survey of 57 enterprise networks, the first large-scale academic study of middlebox deployment. We show that APLOMB solves real problems faced by network administrators, can outsource over 90% of middlebox hardware in a typical large enterprise network, and, in a case study of a real enterprise, imposes an average latency penalty of 1.1ms and median bandwidth inflation of 3.8%.

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The Internet was designed to always find a route if there is a policy-compliant path. However, in many cases, connectivity is disrupted despite the existence of an underlying valid path. The research community has focused on short-term outages that occur during route convergence. There has been less progress on addressing avoidable long-lasting outages. Our measurements show that long-lasting events contribute significantly to overall unavailability. To address these problems, we develop LIFEGUARD , a system for automatic failure localization and remediation. LIFEGUARD uses active measurements and a historical path atlas to locate faults, even in the presence of asymmetric paths and failures. Given the ability to locate faults, we argue that the Internet protocols should allow edge ISPs to steer traffic to them around failures, without requiring the involvement of the network causing the failure. Although the Internet does not explicitly support this functionality today, we show how to approximate it using carefully crafted BGP messages. LIFEGUARD employs a set of techniques to reroute around failures with low impact on working routes. Deploying LIFEGUARD on the Internet, we find that it can effectively route traffic around an AS without causing widespread disruption.

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