In this paper, we presentRoCC, a robust congestion control approach for datacenter networks based on RDMA.RoCCleverages switch queue size as an input to a PI controller, which computes the fair data rate of flows in the queue. The PI parameters are self-tuning to guarantee stability, rapid convergence, and fair and near-optimal throughput in a wide range of congestion scenarios. Our simulation and DPDK implementation results show thatRoCCcan achieve up to$7\times$reduction in PFC frames generated under high load levels, compared to DCQCN. At the same time,RoCCcan achieve$1.7 - 4.5\times$and$1.4 - 3.9\times$lower tail latency for long flows and$2.1-7\times$and$3.5-8.2\times$lower tail latency for short flows, compared to DCQCN and HPCC, respectively. We also find thatRoCCdoes not require PFC. The functional components ofRoCCcan be efficiently implemented in P4 and FPGA-based switch hardware.

In this paper, we present RoCC, a robust congestion control approach for datacenter networks based on RDMA. RoCC leverages switch queue size as an input to a PI controller, which computes the fair data rate of flows in the queue, signaling it to the flow sources. The PI parameters are self-tuning to guarantee stability, rapid convergence, and fair and near-optimal throughput in a wide range of congestion scenarios. Our simulation and DPDK implementation results show that RoCC can achieve up to 7× reduction in PFC frames generated under high average load levels, compared to DCQCN. At the same time, RoCC can achieve up to 8× lower tail latency, compared to DCQCN and HPCC. We also find that RoCC does not require PFC. The functional components of RoCC are implementable in P4-based and fixed-function switch ASICs.

Buffering architectures and policies for their efficient management are core ingredients of a network architecture. However, despite strong incentives to experiment with and deploy new policies, opportunities for changing anything beyond minor elements are limited. We introduce a new specification language, OpenQueue, that allows to express virtual buffering architectures and management policies representing a wide variety of economic models. OpenQueue allows users to specify entire buffering architectures and policies conveniently through several comparators and simple functions. We show examples of buffer management policies in OpenQueue and empirically demonstrate its impact on performance in various settings.

Buffering architectures and policies for their efficient management constitute one of the core ingredients of a network architecture. However, despite strong incentives to experiment with, and deploy, new policies, the opportunities for alterating anything beyond minor elements of such policies are limited. In this work we introduce a new specification language, OpenQueue, that allows users to specify entire buffering architectures and policies conveniently through several comparators and simple functions. We show examples of buffer management policies in OpenQueue and empirically demonstrate its direct impact on performance in various settings.

Buffering architectures and policies for their efficient management constitute one of the core ingredients of a network architecture. In this work we introduce a new specification language, BASEL, that allows to express virtual buffering architectures and management policies representing a variety of economic models. BASEL does not require the user to implement policies in a high-level language; rather, the entire buffering architecture and its policy are reduced to several comparators and simple functions. We show examples of buffer management policies in BASEL and demonstrate empirically the impact of various settings on performance.