RateMP: Optimizing Bandwidth Utilization with High Burst Tolerance in Data Center Networks

Load balancing in data center networks (DCNs) is a crucial and complex undertaking. Multi-path TCP (MPTCP) has been proposed as a cost-effective solution that aims to distribute workloads and improve network resource utilization. However, it can escalate buffer occupancy and undermine burst tolerance, particularly in scenarios involving incast short flows. To address these limitations, we propose a novel multi-path congestion control algorithm, RateMP, to optimize bandwidth utilization efficiency while ensuring burst tolerance in DCNs. RateMP employs a hybrid window and rate control loop with coupled gradient projection adjustment, enabling fast and fine-grained bandwidth allocation and accelerating convergence. Additionally, RateMP eliminates the limitation of cwnd with under-rate pacing to protect incast and busty flows. We prove that RateMP is Lyapunov stable and asymptotically stable, and show the improvement of RateMP through a kernel-based implementation and extended large-scale simulations. RateMP keeps high bandwidth utilization, cuts RTT by 2x and reduces flow completion times (FCT) by 45% in incast scenarios compared to existing algorithms.