# Inter-Data Center RDMA: Challenges, Status, and Future Directions
## 4 Existing Representative Works
### Comparison  
In this section, several recent RDMA optimization designs for inter-DC scenarios were analyzed and compared. Additionally, representative optimization schemes for non-RDMA-based inter-DC data transmission were evaluated. We mainly compared the properties of \begin{table}
\begin{tabular}{c c c} \hline
**Scheme** & **Optimization Method** & **Innovations** \\ \hline GEMINI [52] & Reactive congestion control & Dual-signal integration for heterogeneous networks; RTT-aware window reduction; adaptive window increase proportional to BDP \\ \hline FlashPass [53] & Proactive congestion control & Sender-driven emulation with time calibration; early data transmission and over-provisioning; adaptive feedback control for emulation traffic \\ \hline GTCP [54] & & Adaptive hybrid mode switching for inter-DC flows; delay-aware pausing mechanism for intra-DC flows \\ \hline IDCC [55] & Hybrid congestion control & Dual-signal PID control for heterogeneous networks; weight function for short flow optimization \\ \hline Annulus [56] & & Dual control loops for heterogeneous bottlenecks; direct feedback-driven rate coordination \\ \hline \end{tabular}
\end{table} 
Table 1: Comparison of non-RDMA inter-DC data transmission optimization methods. these schemes in terms of optimization method, network reliability, implementing location. It is hoped that these analyses will provide valuable references for the design of future inter-DC RDMA solutions. From an optimization perspective, most research efforts focus on congestion control as their primary domain of study. Congestion control algorithms are classified into three categories, including proactive congestion control, reactive congestion control, and hybrid congestion control [57]. Proactive congestion control aims to prevent congestion before it occurs by managing link bandwidth allocation in advance; reactive congestion control adjusts the sending rate in response to congestion signals (e.g., packet loss, RTT, switch queue length, and ECN); hybrid congestion control combines the above two, expecting to integrate the advantages of both proactive and reactive congestion control. As clearly illustrated in Table 2, most inter-DC RDMA optimization schemes use reactive [19; 23] and hybrid [49; 50] congestion control methods, while non-RDMA-specific congestion control schemes encompass reactive [52], proactive [53], and hybrid approaches [54; 55; 56]. Additionally, the congestion control schemes typically employ two types of congestion control loops: those using a single end-to-end congestion control loop [19; 23; 52] and those using multiple congestion control loops [49; 50; 54; 55; 56]. Multiple control loops are typically composed of near-end control loops and end-to-end control loops. Near-end control loops can effectively supplement the slow response of end-to-end control loops. Both RDMA-specific and non-RDMA-specific congestion control optimization methods utilize these two types of congestion control loops. Schemes based on a single end-to-end congestion control loop require less hardware modifications during actual implementation, thereby ensuring better compatibility with existing infrastructure. Solutions designed with multiple control loops evidently provide better performance, as they can instantly detect congestion and quickly relay feedback to the source, allowing for timely rate adjustments; therefore, these methods tend to perform better as the distance of the DCI link increases. In addition to the above optimization methods for congestion control, there are also proactive error correction methods [51] specifically designed for WANs with relatively low bandwidth and high packet loss rate. These methods utilize the FEC mechanism to proactively generate repair packets to deal with packet loss situations in advance instead of passively waiting to handle them after packet loss occurs.