During the past twenty years the Domain Name System (DNS) has sustained phenomenal growth while maintaining satisfactory performance. However, the original design focused mainly on system robustness against physical failures, and neglected the impact of operational errors such as misconfigurations. Our recent measurement effort revealed three specific types of misconfigurations in DNS today: lame delegation, diminished server redundancy, and cyclic zone dependency. Zones with configuration errors suffer from reduced availability and increased query delays up to an order of magnitude. Furthermore, while the original DNS design assumed that redundant DNS servers fail independently, our measurements show that operational choices made at individual zones can severely affect the availability of other zones. We found that, left unchecked, DNS configuration errors are widespread, with lame delegation affecting 15% of the DNS zones, diminished server redundancy being even more prevalent, and cyclic dependency appearing in 2% of the zones. We also noted that the degrees of misconfiguration vary from zone to zone, with most popular zones having the lowest percentage of errors. Our results indicate that DNS, as well as any other truly robust large-scale system, must include systematic checking mechanisms to cope with operational errors.
To serve users quickly, Web service providers build infrastructure closer to clients and use multi-stage transport connections. Although these changes reduce client-perceived round-trip times, TCP's current mechanisms fundamentally limit latency improvements. We performed a measurement study of a large Web service provider and found that, while connections with no loss complete close to the ideal latency of one round-trip time, TCP's timeout-driven recovery causes transfers with loss to take five times longer on average. In this paper, we present the design of novel loss recovery mechanisms for TCP that judiciously use redundant transmissions to minimize timeout-driven recovery. Proactive, Reactive, and Corrective are three qualitatively-different, easily-deployable mechanisms that (1) proactively recover from losses, (2) recover from them as quickly as possible, and (3) reconstruct packets to mask loss. Crucially, the mechanisms are compatible both with middleboxes and with TCP's existing congestion control and loss recovery. Our large-scale experiments on Google's production network that serves billions of flows demonstrate a 23% decrease in the mean and 47% in 99th percentile latency over today's TCP.
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