Optimizing Flow Completion Time via Adaptive Buffer Management in Data Center Networks

The traffic of modern data centers exhibits long-tail distribution, in which massive delay-sensitive short flows and a small number of bandwidth-hungry long flows co-exist. These two types of flows could share same bottleneck links in the data center networks but request different or even opposite network requirements. Existing solutions try to realize a trade-off between the requirements of different flows by either prioritizing short flows or limiting the buffer used by long flows at switches or end-hosts. However, they do not consider the dynamic traffic change and suffer from performance degradation, resulted from severe queueing delay and massive packet drops for short flows under current First-In-First- Out (FIFO) queueing mechanism. In this paper, we propose a novel buffer management scheme at switches, called Cut-in Queue (CQ), to achieve both low latency for short flows and high throughput for long flows. Based on network status in real time, CQ prioritizes short flows by dynamically cutting the short flows' packets into the head of long flows or evicting some enqueued long flows' packets and enables high throughput for long flows in most of the cases. Evaluation of both DPDK testbed and NS2 simulations show that CQ outperforms state-of-the-art buffer management schemes by reducing flow completion time by up to 73%.