Occupancy Sampling for Terabit CEE Switches

Abstract

One consequential feature of Converged Enhanced Ethernet (CEE) is loss lessness, achieved through L2 Priority Flow Control (PFC) and Quantized Congestion Notification (QCN). We focus on QCN and its effectiveness in identifying congestive flows in input-buffered CEE switches. QCN assumes an idealized, output-queued switch, however, as future switches scale to higher port counts and link speeds, purely output-queued or shared-memory architectures lead to excessive memory bandwidth requirements, moreover, PFC typically requires dedicated buffers per input. Our objective is to complement PFC's coarse per-port/priority granularity with QCN's per-flow control. By detecting buffer overload early, QCN can drastically reduce PFC's side effects. We install QCN congestion points (CPs) at input buffers with virtual output queues and demonstrate that arrival-based marking cannot correctly discriminate between culprits and victims. Our main contribution is occupancy sampling (QCN-OS), a novel, QCN-compatible marking scheme. We focus on random occupancy sampling, a practical method not requiring any per-flow state. For CPs with arbitrarily scheduled buffers, QCN-OSis shown to correctly identify congestive flows, improving buffer utilization, switch efficiency, and fairness.