EC4: ECN and CreditReservation Converged Congestion Control Bursty traffic and thousands of concurrent flows incur inevitable congestion in data center networks (DCNs) and then affect the overall performance. Various transport protocols are developed to mitigate the network congestion, including reactive and proactive protocols. Reactive schemes to handling congestion after congestion arises are common to current DCNs. However, with the growth of scale and link speed, reactive schemes such as DCTCP encounter the significant problem of slow responding to congestion. On the contrary, proactive protocols are designed to avoid congestion, and they have the advantages of zero data loss, fast convergence and low bu er occupancy (e.g., creditreservation protocols). But in actual deployment scenario, it is hard to guarantee one protocol to be deployed in every server at one time. When creditreservation protocol is deployed to DCNs stepbystep, the network is converted to multiprotocol state and faces the following fundamental challenges: (i) unfairness, (ii) high bu er occupancy, and (iii) heavy tail delay. Therefore, we propose EC4, which is for converging ECNbased and creditreservation protocols with minimal modification. To the best of our knowledge, EC4 is the first to address how to harmonize proactive and reactive congestion control. Targeting the common ECNbased protocolDCTCP, EC4 leverages the Forward Explicit Congestion Notification (FECN) to deliver realtime congestion information and redefines feedback control. After evaluation, the results show that EC4 e ectively addresses the unfair link allocation. Furthermore, even workloads at 0.6 does not cause buffer overflow, thus largely eliminating the timeouts problem.

informationAgnostic Traffic Scheduling in Data Center Networks with Asymmetric Topologies As more and more applications are deployed in data centers, they rely on high performance data center networks (DCNs) to meet usersxe2x80x99 increasing quality of the experience (QoE) requirements. Hence, minimizing the average flow completion time (FCT) has been one of the most important goals for DCNs. However, existing traffic scheduling methods assume either prior knowledge of flows (i.e., sizes and deadlines) or symmetric topologies (i.e., FatTree or Bcube). In practice, it is difficult to obtain the information of flows. Moreover, even with symmetric topology design, the DCNs will become asymmetric due to the inevitable link failure and congestion. In this case, it is a great challenge to minimize the average FCT in DCNs. In this paper, we propose a flowlet based informationagnostic traffic scheduling mechanism. The key idea of our method is leveraging multiple priority queues in switches to demote the priority of flows dynamically on the flowlet level. More specifically, the priority of a flow will be demoted according to the number of flowlets it has sent, which follows the shortest job first discipline. We formulate the average FCT minimization problem as a nonlinear SumofRatios problem and design two heuristic methods to derive the suboptimal demotion thresholds. Experiment results show that our method can reduce the average FCT by up to 15.35% with a realistic workload, as compared to the stateoftheart traffic scheduling methods.