Cloud services are deployed in datacenters connected though high-bandwidth Wide Area Networks (WANs). We find that WAN traffic negatively impacts the performance of datacenter traffic, increasing tail latency by 2.5x, despite its small bandwidth demand. This behavior is caused by the long round-trip time (RTT) for WAN traffic, combined with limited buffering in datacenter switches. The long WAN RTT forces datacenter traffic to take the full burden of reacting to congestion. Furthermore, datacenter traffic changes on a faster time-scale than the WAN RTT, making it difficult for WAN congestion control to estimate available bandwidth accurately.

We present the design and implementation of p4v, a practical tool for verifying data planes described using the P4 programming language. The design of p4v is based on classic verification techniques but adds several key innovations including a novel mechanism for incorporating assumptions about the control plane and domain-specific optimizations which are needed to scale to large programs. We present case studies showing that p4v verifies important properties and finds bugs in real-world programs. We conduct experiments to quantify the scalability of p4v on a wide range of additional examples. We show that with just a few hundred lines of control-plane annotations, p4v is able to verify critical safety properties for switch.p4, a program that implements the functionality of on a modern data center switch, in under three minutes.

Various topologies have been proposed in the context of high-performance computing and data center networking. Direct-connect topologies generally offer large capacity with high path diversity and are highly cost effective for general data center traffic patterns. However, the lack of simple yet efficient load balancing techniques for direct-connect fabrics has hindered these networks from gaining traction in data centers. This paper presents the design, implementation, and evaluation of Flicr, a light-weight host-based load balancing mechanism for direct-connect data centers. Flicr dynamically reroutes traffic through minimal and non-minimal routes to avoid congesting the fabric. This enables Flicr to efficiently minimize networking resource consumption while exploiting high path diversity in direct-connect fabrics to balance the network and gracefully handle link failures. Flicr requires only a simple kernel modification and is readily deployable in commodity data centers today. Our evaluations show that Flicr consistently outperforms other state-of-the-art load balancing designs, achieving 25-60% lower average flow completion time compared to adaptive routing. Flicr is also more robust against link failures and has 5-8 χ better performance relative to other schemes in the presence of link failures.

In this paper we present pFabric, a minimalistic datacenter transport design that provides near theoretically optimal flow completion times even at the 99th percentile for short flows, while still minimizing average flow completion time for long flows. Moreover, pFabric delivers this performance with a very simple design that is based on a key conceptual insight: datacenter transport should decouple flow scheduling from rate control. For flow scheduling, packets carry a single priority number set independently by each flow; switches have very small buffers and implement a very simple priority-based scheduling/dropping mechanism. Rate control is also correspondingly simpler; flows start at line rate and throttle back only under high and persistent packet loss. We provide theoretical intuition and show via extensive simulations that the combination of these two simple mechanisms is sufficient to provide near-optimal performance.