Congestion control mechanisms for data center networks
Wei Bai · 2017
Nowadays, data centers are being built around the world to provide infrastructure support for big data and cloud computing. Many data center applications such as web search, recommendation systems, social networking, etc., have very demanding latency requirements. Even a small delay due to network congestion can directly affect application performance and degrade user experience. Therefore, handling the network congestion in data centers is critical. This thesis focuses on congestion control mechanisms for data center networks. Specifically, we make the following three key contributions. First, we present PIAS, a flow scheduling mechanism to minimize the average flow completion time. PIAS differs from most prior solutions in that it: 1) does not assume prior knowledge of flow size information; and 2) can be readily implemented with commodity switch hardware and legacy network stacks. Second, we reveal that existing Explicit Congestion Notification (ECN) marking schemes suffer from severe performance impairments in multi-service multi-queue data centers. Then we propose MQ-ECN, a new ECN marking scheme for multi-queue with round-robin scheduling, which is widely used in production data centers. Moreover, driven by recent progress in programmable schedulers, we further design TCN that enables ECN for multi-queue with arbitrary scheduling. Third, we observe that existing transport solutions suffer from either excessive packet losses or serious throughput degradation in high-speed extremely shallow-buffered data center networks. Then we propose BCC, a simple yet effective solution with only one more ECN configuration at the switch. BCC maintains low packet loss rate persistently while keeping high throughput until the buffer becomes insufficient.